Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It With Pride. Together with analytics team leaders you will support our business with excellent data models to uncover trends that can drive long-term business results. How You Will Contribute You will: Work in close partnership with the business leadership team to execute the analytics agenda Identify and incubate best-in-class external partners to drive delivery on strategic projects Develop custom models/algorithms to uncover signals/patterns and trends to drive long-term business performance Execute the business analytics program agenda using a methodical approach that conveys to stakeholders what business analytics will deliver What You Will Bring A desire to drive your future and accelerate your career and the following experience and knowledge: Using data analysis to make recommendations to senior leaders Technical experience in roles in best-in-class analytics practices Experience deploying new analytical approaches in a complex and highly matrixed organization Savvy in usage of the analytics techniques to create business impacts In this role, you will be a key technical leader in developing our cutting-edge Supply Chain Data Product ecosystem. You'll have the opportunity to design, build, and automate data ingestion, harmonization, and transformation processes, driving advanced analytics, reporting, and insights to optimize Supply Chain performance across the organization. You will play an instrumental part in engineering robust and scalable data solutions, acting as a hands-on expert for Supply Chain data, and contributing to how these data products are visualized and interacted with. What you need to know about this position: Our team is at the forefront of building Data Products driving AI and Analytics across Mondelez. As a Sr. Data & Analytics Engineer within the Mondelez Data Product team, you will be working towards the following objectives: Build and Enhance Supply Chain Data Products: Design, develop, and maintain reusable Data Products as the single source of truth for Supply Chain, logistics, manufacturing, and related data domains. End-to-End Data Pipeline Development: Leverage data from diverse internal systems (especially SAP ECC/S4HANA, SAP BW/HANA, and other Supply Chain platforms) and external data sources, ingesting it into our centralized Google Cloud Platform (GCP) data platform. Enable Data Governance and Management: Implement and champion Data Governance and Data Management standards, including data cataloging, documentation, security protocols, robust data quality controls, master data management (MDM) principles, and data democratization. Scalable Data Modeling & Implementation: Design, implement, and optimize reusable and scalable data models following industry best practices and high coding standards, ensuring efficient data flow for analytical consumption. Hands-on Technical Leadership: Play a lead technical role throughout the entire Software Development Lifecycle (SDLC) – from requirements gathering and design to development, testing, deployment, and hypercare. Product and Value-Driven Mindset: Build each feature with a Product Owner mindset, focusing on delivering business value with efficiency, agility, and a strong bias for action. This includes considering the end-user experience of the data products. Technical Point of Contact: Act as a key technical expert and point of contact within the Data Engineering team for Supply Chain data initiatives. What extra ingredients you will bring: Proven hands-on experience designing and developing complex data models and high-quality, performant data pipelines. Passion for leveraging data to drive tangible improvements in Supply Chain efficiency, cost reduction, and operational excellence. Ability to thrive in an entrepreneurial, fast-paced setting, managing complex data challenges with a solutions-oriented approach. Excellent communication and collaboration skills to facilitate effective teamwork, engage with Supply Chain stakeholders, and explain complex data concepts to both technical and non-technical individuals. Strong problem-solving skills and business acumen, particularly within the Supply Chain domain. Education / Certifications: Bachelor's degree in Information Systems/Technology, Computer Science, Analytics, Engineering, or a related field. 10+ years of hands-on experience in data engineering, data warehousing, or a similar technical role, preferably in CPG or manufacturing with a strong focus on Supply Chain data. Job specific requirements (Hands-on Experience Focus): SAP Data Expertise: Deep hands-on experience in extracting, transforming, and modeling data from SAP ECC/S4HANA (modules like MM, SD, PP, QM, FI/CO) and SAP BW/HANA. Proven ability to understand SAP data structures and business processes within Supply Chain. Data Pipeline Development: Design, build, and maintain robust and efficient ETL/ELT processes for data integration, ensuring data accuracy, integrity, and timeliness. Cloud Data Engineering (GCP Focused): Strong proficiency and hands-on experience in data warehousing solutions and data engineering services within the Google Cloud Platform (GCP) ecosystem (e.g., BigQuery, Dataflow, Dataproc, Cloud Composer, Pub/Sub). Hands-on experience with Databricks (ideally deployed on GCP or with GCP integration) for large-scale data processing, Spark-based transformations, and advanced analytics is highly desirable. Data Modeling & Warehousing: Hands-on experience in developing efficient data models (e.g., dimensional, Data Vault) and building/maintaining data warehouses, primarily on GCP. Programming & Automation: Strong proficiency in SQL and Python for data manipulation, pipeline development, and automation. API Integration: Experience working with multiple APIs to extract and/or send data for system integration. BI & Analytics Enablement: Collaborate with data scientists, analysts, and business users to provide high-quality, reliable data for their analyses and models. Support the development of data consumption layers, including dashboards (e.g., Tableau, Power BI). UI/Front-End Experience (Desirable): Experience with front-end technologies and JavaScript frameworks (e.g., React JS, Angular, Vue.js) for building custom data visualizations, interactive dashboards, or user interfaces for Data Products is a significant plus. System Monitoring & Optimization: Monitor data processing systems and pipelines to ensure efficiency, reliability, performance, and uptime; proactively identify and resolve bottlenecks. DevOps & CI/CD: Prior hands-on work in a DevOps environment or strong understanding and experience implementing CI/CD pipelines for data solutions Data Governance & Security: Ensure compliance with data privacy regulations and implement data security standards and best practices within data solutions on GCP. Industry Knowledge: Solid understanding of the consumer goods industry, particularly Supply Chain processes and relevant key performance indicators (KPIs). Agile Methodologies: Experience working in Agile development environments. Continuous Learning: Stay updated on the latest technologies and best practices in data engineering, GCP data services, Databricks, UI development trends, and database management. Within Country Relocation support available and for candidates voluntarily moving internationally some minimal support is offered through our Volunteer International Transfer Policy Business Unit Summary At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about. We have a rich portfolio of strong brands globally and locally including many household names such as Oreo , belVita and LU biscuits; Cadbury Dairy Milk , Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum. Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen—and happen fast. Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Job Type Regular Analytics & Modelling Analytics & Data Science Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 5.00 + years Salary : Confidential (based on experience) Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full time Permanent Position (*Note: This is a requirement for one of Uplers' client - Forbes Advisor) What do you need for this opportunity? Must have skills required: Python, Postgre SQL, Snowflake, AWS RDS, BigQuery, OOPs, Monitoring tools, Prometheus, ETL tools, Data warehouse, Pandas, Pyspark, AWS Lambda Forbes Advisor is Looking for: Job Description: Data Research - Database Engineer Forbes Advisor is a new initiative for consumers under the Forbes Marketplace umbrella that provides journalist- and expert-written insights, news and reviews on all things personal finance, health, business, and everyday life decisions. We do this by providing consumers with the knowledge and research they need to make informed decisions they can feel confident in, so they can get back to doing the things they care about most. Position Overview At Marketplace, our mission is to help readers turn their aspirations into reality. We arm people with trusted advice and guidance, so they can make informed decisions they feel confident in and get back to doing the things they care about most. We are an experienced team of industry experts dedicated to helping readers make smart decisions and choose the right products with ease. Marketplace boasts decades of experience across dozens of geographies and teams, including Content, SEO, Business Intelligence, Finance, HR, Marketing, Production, Technology and Sales. The team brings rich industry knowledge to Marketplace’s global coverage of consumer credit, debt, health, home improvement, banking, investing, credit cards, small business, education, insurance, loans, real estate and travel. The Data Research Engineering Team is a brand new team with the purpose of managing data from acquisition to presentation, collaborating with other teams while also operating independently. Their responsibilities include acquiring and integrating data, processing and transforming it, managing databases, ensuring data quality, visualizing data, automating processes, working with relevant technologies, and ensuring data governance and compliance. They play a crucial role in enabling data-driven decision-making and meeting the organization's data needs. A typical day in the life of a Database Engineer/Developer will involve designing, developing, and maintaining a robust and secure database infrastructure to efficiently manage company data. They collaborate with cross-functional teams to understand data requirements and migrate data from spreadsheets or other sources to relational databases or cloud-based solutions like Google BigQuery and AWS. They develop import workflows and scripts to automate data import processes, optimize database performance, ensure data integrity, and implement data security measures. Their creativity in problem-solving and continuous learning mindset contribute to improving data engineering processes. Proficiency in SQL, database design principles, and familiarity with Python programming are key qualifications for this role. Responsibilities: Design, develop, and maintain the database infrastructure to store and manage company data efficiently and securely. Work with databases of varying scales, including small-scale databases, and databases involving big data processing. Work on data security and compliance, by implementing access controls, encryption, and compliance standards. Collaborate with cross-functional teams to understand data requirements and support the design of the database architecture. Migrate data from spreadsheets or other sources to a relational database system (e.g., PostgreSQL, MySQL) or cloud-based solutions like Google BigQuery. Develop import workflows and scripts to automate the data import process and ensure data accuracy and consistency. Optimize database performance by analyzing query execution plans, implementing indexing strategies, and improving data retrieval and storage mechanisms. Work with the team to ensure data integrity and enforce data quality standards, including data validation rules, constraints, and referential integrity. Monitor database health and identify and resolve issues. Collaborate with the full-stack web developer in the team to support the implementation of efficient data access and retrieval mechanisms. Implement data security measures to protect sensitive information and comply with relevant regulations. Demonstrate creativity in problem-solving and contribute ideas for improving data engineering processes and workflows. Embrace a learning mindset, staying updated with emerging database technologies, tools, and best practices. Explore third-party technologies as alternatives to legacy approaches for efficient data pipelines. Familiarize yourself with tools and technologies used in the team's workflow, such as Knime for data integration and analysis. Use Python for tasks such as data manipulation, automation, and scripting. Collaborate with the Data Research Engineer to estimate development efforts and meet project deadlines. Assume accountability for achieving development milestones. Prioritize tasks to ensure timely delivery, in a fast-paced environment with rapidly changing priorities. Collaborate with and assist fellow members of the Data Research Engineering Team as required. Perform tasks with precision and build reliable systems. Leverage online resources effectively like StackOverflow, ChatGPT, Bard, etc., while considering their capabilities and limitations. Skills And Experience Bachelor's degree in Computer Science, Information Systems, or a related field is desirable but not essential. Experience with data warehousing concepts and tools (e.g., Snowflake, Redshift) to support advanced analytics and reporting, aligning with the team’s data presentation goals. Skills in working with APIs for data ingestion or connecting third-party systems, which could streamline data acquisition processes. Proficiency with tools like Prometheus, Grafana, or ELK Stack for real-time database monitoring and health checks beyond basic troubleshooting. Familiarity with continuous integration/continuous deployment (CI/CD) tools (e.g., Jenkins, GitHub Actions). Deeper expertise in cloud platforms (e.g., AWS Lambda, GCP Dataflow) for serverless data processing or orchestration. Knowledge of database development and administration concepts, especially with relational databases like PostgreSQL and MySQL. Knowledge of Python programming, including data manipulation, automation, and object-oriented programming (OOP), with experience in modules such as Pandas, SQLAlchemy, gspread, PyDrive, and PySpark. Knowledge of SQL and understanding of database design principles, normalization, and indexing. Knowledge of data migration, ETL (Extract, Transform, Load) processes, or integrating data from various sources. Knowledge of cloud-based databases, such as AWS RDS and Google BigQuery. Eagerness to develop import workflows and scripts to automate data import processes. Knowledge of data security best practices, including access controls, encryption, and compliance standards. Strong problem-solving and analytical skills with attention to detail. Creative and critical thinking. Strong willingness to learn and expand knowledge in data engineering. Familiarity with Agile development methodologies is a plus. Experience with version control systems, such as Git, for collaborative development. Ability to thrive in a fast-paced environment with rapidly changing priorities. Ability to work collaboratively in a team environment. Good and effective communication skills. Comfortable with autonomy and ability to work independently. Perks: Day off on the 3rd Friday of every month (one long weekend each month) Monthly Wellness Reimbursement Program to promote health well-being Monthly Office Commutation Reimbursement Program Paid paternity and maternity leaves How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Role Description Key Responsibilities Design, develop, and optimize ETL pipelines using PySpark on Google Cloud Platform (GCP). Work with BigQuery, Cloud Dataflow, Cloud Composer (Apache Airflow), and Cloud Storage for data transformation and orchestration. Develop and optimize Spark-based ETL processes for large-scale data processing. Implement best practices for data governance, security, and monitoring in a cloud environment. Collaborate with data engineers, analysts, and business stakeholders to understand data requirements. Troubleshoot performance bottlenecks and optimize Spark jobs for efficient execution. Automate data workflows using Apache Airflow or Cloud Composer. Ensure data quality, validation, and consistency across pipelines. 5+ years of experience in ETL development with a focus on PySpark. Strong hands-on experience with Google Cloud Platform (GCP) services, including: BigQuery Cloud Dataflow / Apache Beam Cloud Composer (Apache Airflow) Cloud Storage Proficiency in Python and PySpark for big data processing. Experience with data lake architectures and data warehousing concepts. Knowledge of SQL for data querying and transformation. Experience with CI/CD pipelines for data pipeline automation. Strong debugging and problem-solving skills. Experience with Kafka or Pub/Sub for real-time data processing. Knowledge of Terraform for infrastructure automation on GCP. Experience with containerization (Docker, Kubernetes). Familiarity with DevOps and monitoring tools like Prometheus, Stackdriver, or Datadog. Skills Gcp,Pyspark,Etl Show more Show less

We are looking for a skilled Lead Data Engineer to enhance our dynamic team. In this role, you will focus on designing, developing, and maintaining data integration solutions for our clients. Your leadership will guide a team of engineers in delivering scalable, high-quality, and efficient data integration solutions. This role is perfect for an experienced data integration expert who is passionate about technology and excels in a fast-paced, dynamic setting. Responsibilities Design, develop, and maintain data integration solutions for clients Lead a team of engineers to ensure high-quality, scalable, and efficient delivery of data integration solutions Collaborate with cross-functional teams to comprehend business requirements and design fitting data integration solutions Ensure the security, reliability, and efficiency of data integration solutions Develop and maintain documentation, including technical specifications, data flow diagrams, and data mappings Continuously update knowledge on the latest data integration methods and tools Requirements Bachelor's degree in Computer Science, Information Systems, or a related field 8-13 years of experience in data engineering, data integration, or a related field Proficiency in cloud-native or Spark-based ETL tools such as AWS Glue, Azure Data Factory, or GCP Dataflow Strong knowledge of SQL for querying and manipulating data Competency in Snowflake for cloud data warehousing Familiarity with at least one cloud platform such as AWS, Azure, or GCP Experience in leading a team of engineers on data integration projects Good verbal and written communication skills in English at a B2 level Nice to have Background in ETL using Python Show more Show less

Our organization is in search of a seasoned Senior Data Engineer to enhance our team. In this role, you will focus on projects involving data integration and ETL for cloud environments. Your primary duties will include the design and execution of intricate data solutions, maintaining data accuracy, dependability, and accessibility. Responsibilities Design and execute intricate data solutions for cloud environments Develop ETL processes utilizing SQL, Python, and other applicable technologies Maintain data accuracy, dependability, and accessibility for all stakeholders Work collaboratively with cross-functional teams to comprehend data integration necessities and specifications Create and uphold documentation such as technical specifications, data flow diagrams, and data mappings Optimize data integration processes for enhanced performance and efficiency while ensuring data accuracy and integrity Requirements Bachelor's degree in Computer Science, Electrical Engineering, or related field 5-8 years of experience in data engineering Proficiency in cloud-native or Spark-based ETL tools like AWS Glue, Azure Data Factory, or GCP Dataflow Strong knowledge of SQL for data querying and manipulation Familiarity with Snowflake for data warehousing Background in cloud platforms such as AWS, GCP, or Azure for data storage and processing Excellent problem-solving skills and meticulous attention to detail Good verbal and written communication skills in English at a B2 level Nice to have Background in ETL using Python Show more Show less

Job Role: Senior Data Analytics Engineer – GCP Experience: 5+ years Location: Noida & Bhubaneswar We are seeking a highly skilled Senior Data Analytics Specialist with deep expertise in Google Cloud Platform (GCP) tools to join our dynamic team. The ideal candidate will have strong experience in data analytics, business intelligence , and advanced data processing on GCP, specifically with Firebase Analytics , GA4 , and BigQuery . Key Responsibilities: Lead and execute data analytics projects leveraging GCP services, primarily focusing on Firebase Analytics and Google Analytics 4 (GA4). Design, develop, and optimize complex SQL queries and scripts in BigQuery for large-scale data processing. Build and maintain interactive dashboards and data models using Looker or Looker Studio. Collaborate with cross-functional teams to implement custom event tracking and user journey analysis. Work with other GCP components such as Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow to streamline data pipelines. Ensure compliance with data privacy and governance standards, including GDPR and CCPA. Analyze data to uncover trends, insights, and opportunities for business improvement. Communicate findings and recommendations clearly to stakeholders across technical and non-technical teams. Required Qualifications: 5 to 7 years of experience in data analytics, business intelligence, or a related domain. Proven expertise with Firebase Analytics and GA4, including custom event configuration and user behavior tracking. Advanced proficiency in BigQuery with experience in SQL scripting, query optimization, partitioning, and clustering. Hands-on experience with Looker or Looker Studio for dashboard creation and data visualization. Familiarity with additional GCP services such as Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow is preferred. Strong understanding of data privacy laws and governance frameworks like GDPR and CCPA. Excellent analytical, problem-solving, and detail-oriented skills. Strong verbal and written communication skills with the ability to work collaboratively across teams. Preferred Qualifications: Google Cloud certifications such as Professional Data Engineer or Looker Business Analyst. Experience working with A/B testing frameworks and experimentation platforms. Background in product analytics or digital marketing analytics. Exceptional communication and stakeholder management skills. Show more Show less

Location: Trivandrum, Bangalore, Chennai, Kochi Job Description : Responsibilities include : - Design and implement scalable, secure, and cost-effective data architectures using GCP. - Lead the design and development of data pipelines with BigQuery, Dataflow, and Cloud Storage. - Architect and implement data lakes, data warehouses, and real-time data processing solutions on GCP. - Ensure data architecture aligns with business goals, governance, and compliance requirements. - Collaborate with stakeholders to define data strategy and roadmap. - Design and deploy BigQuery solutions for optimized performance and cost efficiency. - Build and maintain ETL/ELT pipelines for large-scale data processing. - Leverage Cloud Pub/Sub, Dataflow, and Cloud Functions for real-time data integration. Requirement : - 10 years of experience in data engineering, with at least 6 years in GCP - Expertise in BigQuery, Cloud Dataflow, Cloud Pub/Sub, Cloud Storage, and related GCP services. - Strong experience in data warehousing, data lakes, and real-time data pipelines. - Proficiency in SQL, Python, or other data processing languages. - Experience with cloud security, data governance, and compliance frameworks. - Strong problem-solving skills and ability to architect solutions for complex data environments. - Google Cloud Certification (Professional Data Engineer, Professional Cloud Architect) preferred. - Leadership experience and ability to mentor technical teams. - Excellent communication and collaboration skills. - Immediate joiner (15 days NP max) Salary Up to 30LPA (not negotiable) Show more Show less

_VOIS Intro About _VOIS: _VO IS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value and enhancing quality and efficiency across 28 countries, and operating from 7 locations: Albania, Egypt, Hungary, India, Romania, Spain and the UK. Over 29,000 highly skilled individuals are dedicated to being Vodafone Group’s partner of choice for talent, technology, and transformation. We deliver the best services across IT, Business Intelligence Services, Customer Operations, Business Operations, HR, Finance, Supply Chain, HR Operations, and many more. Established in 2006, _VO IS has evolved into a global, multi-functional organisation, a Centre of Excellence for Intelligent Solutions focused on adding value and delivering business outcomes for Vodafone. _VOIS Centre Intro About _VOIS India: In 2009, _VO IS started operating in India and now has established global delivery centres in Pune, Bangalore and Ahmedabad. With more than 14,500 employees, _VO IS India supports global markets and group functions of Vodafone, and delivers best-in-class customer experience through multi-functional services in the areas of Information Technology, Networks, Business Intelligence and Analytics, Digital Business Solutions (Robotics & AI), Commercial Operations (Consumer & Business), Intelligent Operations, Finance Operations, Supply Chain Operations and HR Operations and more. Job Role Related Content (Role specific) Key Responsibilities Design, develop, and maintain scalable data pipelines and ETL processes using GCP services such as BigQuery, Cloud Data Fusion, Dataflow, Pub/Sub, Cloud Storage, Composer ,Cloud Function, Cloud RUN Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver high-quality data solutions. Implement data integration solutions to ingest, process, and store large volumes of structured and unstructured data from various sources. Optimize and tune data pipelines for performance, reliability, and cost-efficiency. Ensure data quality and integrity through data validation, cleansing, and transformation processes. Develop and maintain data models, schemas, and metadata to support data analytics and reporting. Monitor and troubleshoot data pipeline issues, ensuring timely resolution and minimal disruption to data workflows. Stay up-to-date with the latest GCP technologies and best practices, and provide recommendations for continuous improvement. Mentor and guide junior data engineers, fostering a culture of knowledge sharing and collaboration. Proficiency in GCP services such as BigQuery, Cloud Data Fusion, Dataflow, Pub/Sub, Cloud Storage, Composer ,Cloud Function, Cloud RUN. Strong programming skills in Python, PLSQL. Experience with SQL and NoSQL databases. Knowledge of data warehousing concepts and best practices. Familiarity with data integration tools and frameworks. _VOIS Equal Opportunity Employer Commitment India _VO IS is proud to be an Equal Employment Opportunity Employer. We celebrate differences and we welcome and value diverse people and insights. We believe that being authentically human and inclusive powers our employees’ growth and enables them to create a positive impact on themselves and society. We do not discriminate based on age, colour, gender (including pregnancy, childbirth, or related medical conditions), gender identity, gender expression, national origin, race, religion, sexual orientation, status as an individual with a disability, or other applicable legally protected characteristics. As a result of living and breathing our commitment, our employees have helped us get certified as a Great Place to Work in India for four years running. We have been also highlighted among the Top 5 Best Workplaces for Diversity, Equity, and Inclusion , Top 10 Best Workplaces for Women , Top 25 Best Workplaces in IT & IT-BPM and 14th Overall Best Workplaces in India by the Great Place to Work Institute in 2023. These achievements position us among a select group of trustworthy and high-performing companies which put their employees at the heart of everything they do. By joining us, you are part of our commitment. We look forward to welcoming you into our family which represents a variety of cultures, backgrounds, perspectives, and skills! Apply now, and we’ll be in touch! Show more Show less

Job Title: Data Architect / Delivery Lead Job Summary: The Data Architect / Delivery Lead will provide technical expertise in the analysis, design, development, rollout, and maintenance of enterprise data models and solutions, utilizing both traditional and emerging technologies such as cloud, Hadoop, NoSQL, and real-time data processing. In addition to technical expertise, the role requires leadership in driving cross-functional teams, ensuring seamless project delivery, and fostering innovation within the team. The candidate must excel in managing data architecture projects while mentoring teams in data engineering practices, including PySpark , automation, and big data integration. Essential Duties Data Architecture Design and Development: Design and develop conceptual, logical, and physical data models for enterprise-scale data lakes and data warehouse solutions, ensuring optimal performance and scalability. Implement real-time and batch data integration solutions using modern tools and technologies such as PySpark, Hadoop, and cloud-based solutions (e.g., AWS, Azure, Google Cloud). Utilize PySpark for distributed data processing, transforming and analyzing large datasets for improved data-driven decision-making. Understand and apply modern data architecture philosophies such as Data Vault, Dimensional Modeling, and Data Lake design for building scalable and sustainable data solutions. Leadership & Delivery Management: Provide leadership in data architecture and engineering projects, ensuring the integration of modern technologies and best practices in data management and transformation. Act as a trusted advisor, collaborating with business users, technical staff, and project managers to define requirements and deliver high-quality data solutions. Lead and mentor a team of data engineers, ensuring the effective application of PySpark for data engineering tasks, and supporting continuous learning and improvement within the team. Manage end-to-end delivery of data projects, including defining timelines, managing resources, and ensuring timely, high-quality delivery while adhering to project methodologies (e.g., Agile, Scrum). Data Movement & Integration: Provide expertise in data integration processes, including batch and real-time data processing using tools such as PySpark, Informatica PowerCenter, SSIS, MuleSoft, and DataStage. Develop and optimize ETL/ELT pipelines, utilizing PySpark for efficient data processing and transformation at scale, particularly for big data environments (e.g., Hadoop ecosystems). Oversee data migration efforts, ensuring high-quality and consistent data delivery while managing data transformation and cleansing processes. Documentation & Communication: Create comprehensive functional and technical documentation, including data integration architecture documentation, data models, data dictionaries, and testing plans. Collaborate with business stakeholders and technical teams to ensure alignment and provide technical guidance on data-related decisions. Prepare and present technical content and architectural decisions to senior management, ensuring clear communication of complex data concepts. Skills and Experience: Data Engineering Skills: Extensive experience in PySpark for large-scale data processing, data transformation, and working with distributed systems. Proficient in modern data processing frameworks and technologies, including Hadoop, Spark, and Flink. Expertise in cloud-based data engineering technologies and platforms such as AWS Glue, Azure Data Factory, or Google Cloud Dataflow. Strong experience with data pipelines, ETL/ELT frameworks, and automation techniques using tools like Airflow, Apache NiFi, or dbt. Expertise in working with big data technologies and frameworks for both structured and unstructured data. Data Architecture and Modeling: 5-10 years of experience in enterprise data modeling, including hands-on experience with ERwin, ER/Studio, PowerDesigner, or similar tools. Strong knowledge of relational databases (e.g., Oracle, SQL Server, Teradata) and NoSQL technologies (e.g., MongoDB, Cassandra). In-depth understanding of data warehousing and data integration best practices, including dimensional modeling and working with OLTP systems and OLAP cubes. Experience with real-time data architectures and cloud-based data lakes, leveraging AWS, Azure, or Google Cloud platforms. Leadership & Delivery Skills: 3-5 years of management experience leading teams of data engineers and architects, ensuring alignment of team goals with organizational objectives. Strong leadership qualities such as innovation, critical thinking, communication, time management, and the ability to collaborate effectively across teams and stakeholders. Proven ability to act as a delivery lead for data projects, driving projects from concept to completion while managing resources, timelines, and deliverables. Ability to mentor and coach team members in both technical and professional growth, fostering a culture of knowledge sharing and continuous improvement. Other Essential Skills: Strong knowledge of SQL, PL/SQL, and proficiency in scripting for data engineering tasks. Ability to translate business requirements into technical solutions, ensuring that the data solutions support business strategies and objectives. Hands-on experience with metadata management, data governance, and master data management (MDM) principles. Familiarity with modern agile methodologies, such as Scrum or Kanban, to ensure iterative and successful project delivery. Preferred Skills & Experience: Cloud Technologies: Experience with cloud data platforms such as AWS Redshift, Google BigQuery, or Azure Synapse for building scalable data solutions. Leadership: Demonstrated ability to build and lead cross-functional teams, drive innovation, and solve complex data problems. Business Consulting: Consulting experience working with clients to deliver tailored data solutions, providing expert guidance on data architecture and data management practices. Data Profiling and Analysis: Hands-on experience with data profiling tools and techniques to assess and improve the quality of enterprise data. Real-Time Data Processing: Experience in real-time data integration and streaming technologies, such as Kafka and Kinesis. Show more Show less

We are looking for a talented Frontend Developer to contribute to our core product development. You will be involved in the full software development lifecycle, building scalable and user-friendly applications. Responsibilities Develop and maintain user-facing features using modern web technologies, such as React.js . Collaborate with designers and product managers to translate design mockups and user stories into responsive and engaging web applications. Optimize application performance and ensure cross-browser compatibility. Implement best practices and coding standards to ensure high-quality and maintainable code. Participate in code reviews and provide constructive feedback to improve code quality. Stay up-to-date with the latest industry trends and technologies to drive innovation in frontend development. Requirements Strong proficiency in HTML, CSS, and JavaScript. Experience in building web applications using React.js . Familiarity with RESTful APIs and integrating frontend applications with backend services. Understanding of responsive design principles and mobile-first development. Knowledge of version control systems, such as Git. Ability to work collaboratively in an Agile/Scrum development environment. Excellent problem-solving and communication skills. This job was posted by Sharan Mithran from The DataFlow Group. Show more Show less

Skill & Experience Strategic Planning and Direction Maintain architecture principles, guidelines and standards Project & Program Management Data Warehousing Big Data Data Analytics &; Data Science for solutioning Expert in Big Query, Dataproc, Data Fusion, Dataflow, Bigtable, Fire Store, CloudSQL, Cloud Spanner, Google Cloud Storage, Cloud Composer, Cloud Interconnect, Etc Strong Experience in Big Data- Data Modelling, Design, Architecting & Solutioning Understands programming language like SQL, Python, R-Scala. Good Python skills, - Experience from data visualisation tools such as Google Data Studio or Power BI Knowledge in A/B Testing, Statistics, Google Cloud Platform, Google Big Query, Agile Development, DevOps, Date Engineering, ETL Data Processing Strong Migration experience of production Hadoop Cluster to Google Cloud. Experience in designing & mplementing solution in mentioned areas:Strong Google Cloud Platform Data Components BigQuery, BigTable, CloudSQL, Dataproc, Data Flow, Data Fusion, Etc

Job Description We are seeking an experienced Director to lead a team responsible for the development and maintenance of our Connected Vehicle Data. The ideal candidate will have a strong technical background in data and/or software engineering, along with proven leadership and management skills. This role requires the ability to design and code streaming solutions, prioritize team tasks, make timely decisions, and guide the team to deliver high-quality results. The leader must be knowledgeable in data governance, customer consent, and security standards. Responsibilities Responsibilities: Lead and mentor a high-performing team of local and remote data engineers. Prioritize team workload, allocate tasks effectively, and ensure team members have the resources to succeed. Provide technical expertise and guidance to the team. Evaluate and mentor adherence to coding standards, best practices, and architectural guidelines. Oversee the design, development, maintenance, scalability, reliability, and performance of the connected vehicle data platform pipelines and architecture. Contribute to the long-term strategic direction of the Connected Vehicle Data Platform with a focus on enterprise use. Enforce and ensure data quality, data governance, and security standards. Collaborate with Data Program Management to prioritize and implement various business customers’ requests and logic into data assets with optimized design and code development. Collaborate to identify and consolidate common tasks across teams to improve efficiency and reduce redundancy. Communicate decisions effectively and transparently to internal and external customers. Stay updated on industry trends and emerging technologies to inform technical decisions. Qualifications Qualifications Required: Minimum – Bachelor’s Degree in Computer Science, Information Technology, Information Systems, or Data Analytics. Preferred – Master’s Degree in highly technical field – computer science, mathematics, physics. 15+ years of experience in data engineering, cloud platforms, or enterprise-scale data management, with a minimum of 5 years in connected/streaming vehicle platforms. 5+ years' experience leading a software/data engineering team. Expertise in one of the following public cloud environments: Amazon Web Services, Google Cloud Platform, or Microsoft Azure. Expert knowledge and hands on experience in DevOps and SDLC. Monitor and optimize cost and compute for processes in GCP technologies (e.g., BigQuery, Dataflow, Cloud Run, DataProc). Manage and scale serverless applications and clusters, optimizing resource utilization, and implementing monitoring and logging strategies. Expertise in streaming technologies (Kafka, Pub/Sub) and OpenShift, managing high-throughput topics, message ordering, and ensuring data consistency and durability. Why Join Ford? Be at the forefront of Ford’s data and AI transformation , influencing how data drives business decisions. Work in a fast-paced, innovation-driven environment with cutting-edge technology and industry-leading experts . Enjoy a culture that values collaboration, inclusion, and career development . Competitive compensation, benefits, and opportunities for professional growth. Join Us in Shaping the Future of Data at Ford! Show more Show less

As a Data Engineer with a focus on migrating on-premises databases to Google Cloud SQL, you will play a critical role in solving complex problems and creating value for our business by ensuring reliable, scalable,and efficient data migration processes. You will be responsible for architecting,designing and implementing custom pipelines on the GCP stack to facilitate seamless migration. Required Skills: 5+ years of industry experience in data engineering, business intelligence, or a related field with experience in manipulating, processing, and extracting value from datasets. Expertise in architecting, designing, building, and deploying internal applications to support technology life cycle management, service delivery management, data, and business intelligence. Experience in developing modular code for versatile pipelines or complex ingestion frameworks aimed at loading data into Cloud SQL and managing data migration from multiple on-premises sources. Strong collaboration with analysts and business process owners to translate business requirements into technical solutions. Proficiency in coding with scripting languages (Shell scripting, Python, SQL). Deep understanding and hands-on experience with Google Cloud Platform (GCP) technologies, especially in data migration and warehousing, including Database Migration Service (DMS), Cloud SQL, BigQuery, Dataflow, Data Catalog, Cloud Composer, Google Cloud Storage (GCS), IAM, Compute Engine, Cloud Data Fusion, and optionally Dataproc. Adherence to best development practices including technical design, solution development, systems configuration, test documentation/execution, issue identification and resolution, and writing clean, modular, self-sustaining code. Familiarity with CI/CD processes using GitHub, Cloud Build, and Google Cloud SDK.

As a Data Engineer, you will design, develop, and support data pipelines and related data products and platforms. Your primary responsibilities include designing and building data extraction, loading, and transformation pipelines across on-prem and cloud platforms. You will perform application impact assessments, requirements reviews, and develop work estimates. Additionally, you will develop test strategies and site reliability engineering measures for data products and solutions, participate in agile development "scrums" and solution reviews, mentor junior Data Engineering Specialists, lead the resolution of critical operations issues, and perform technical data stewardship tasks, including metadata management, security, and privacy by design. Required Skills: Design, develop, and support data pipelines and related data products and platforms. Design and build data extraction, loading, and transformation pipelines and data products across on-prem and cloud platforms. Perform application impact assessments, requirements reviews, and develop work estimates. Develop test strategies and site reliability engineering measures for data products and solutions. Participate in agile development "scrums" and solution reviews. Mentor junior Data Engineers. Lead the resolution of critical operations issues, including post-implementation reviews. Perform technical data stewardship tasks, including metadata management, security, and privacy by design. Design and build data extraction, loading, and transformation pipelines using Python and other GCP Data Technologies Demonstrate SQL and database proficiency in various data engineering tasks. Automate data workflows by setting up DAGs in tools like Control-M, Apache Airflow, and Prefect. Develop Unix scripts to support various data operations. Model data to support business intelligence and analytics initiatives. Utilize infrastructure-as-code tools such as Terraform, Puppet, and Ansible for deployment automation. Expertise in GCP data warehousing technologies, including BigQuery, Cloud SQL, Dataflow, Data Catalog, Cloud Composer, Google Cloud Storage, IAM, Compute Engine, Cloud Data Fusion and Dataproc (good to have).

Required Skills & Qualifications: Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline. Minimum of 5 years of practical experience in a data engineering or comparable position. Demonstrated expertise in SQL and Python (or similar languages such as Scala/Java). Extensive experience with data pipeline orchestration tools (e.g., Airflow, dbt, ). Proficiency in cloud data platforms, including AWS (Redshift, S3, Glue), or GCP (BigQuery, Dataflow), or Azure (Data Factory, Synapse). Familiarity with big data technologies (e.g., Spark, Kafka, Hive) and other data tools. Solid grasp of data warehousing principles, data modeling techniques, and performance tuning. (e.g. Erwin Data Modeler, MySQL Workbench) · Exceptional problem-solving abilities coupled with a proactive and team-oriented approach. Show more Show less

Our organization is seeking a skilled Senior Data Engineer to become an integral part of our team. In this role, you will focus on projects related to data integration and ETL on cloud-based platforms. You will take charge of creating and executing sophisticated data solutions, ensuring data accuracy, dependability, and accessibility. Responsibilities Create and execute sophisticated data solutions on cloud-based platforms Build ETL processes utilizing SQL, Python, and other applicable technologies Maintain data accuracy, reliability, and accessibility for all stakeholders Work with cross-functional teams to comprehend data integration needs and specifications Produce and sustain documentation, including technical specifications, data flow diagrams, and data mappings Enhance and tune data integration processes for optimal performance and efficiency, guaranteeing data accuracy and integrity Requirements Bachelor’s degree in Computer Science, Electrical Engineering, or a related field 5-8 years of experience in data engineering Proficiency in cloud-native or Spark-based ETL tools such as AWS Glue, Azure Data Factory, or GCP Dataflow Strong knowledge of SQL for data querying and manipulation Qualifications in Snowflake for data warehousing Familiarity with cloud platforms like AWS, GCP, or Azure for data storage and processing Excellent problem-solving skills and attention to detail Good verbal and written communication skills in English at a B2 level Nice to have Background in ETL using Python Show more Show less

The Technical Lead / Technical Consultant is a core role and focal point of the project team responsible for the whole technical solution and managing the day-to-day delivery. The role will focus on the technical solution architecture, detailed technical design, coaching of the development/implementation team, and governance of the technical delivery. Technical ownership of the solution from bid inception through implementation to client delivery, followed by after-sales support and best practice advice. Interactions with internal stakeholders and clients to explain technology solutions and a clear understanding of client’s business requirements through which to guide optimal design to meet their needs. Job Description: Must-Have Skills: Database (one or more of MS SQL Server, Oracle, Cloud SQL, Cloud Spanner, etc.) Data Warehouse (one or more of Big Query, SnowFlake, etc.) ETL tool (two or more of Cloud Data Fusion, Dataflow, Dataproc, Pub/Sub, Composer, Cloud Functions, Cloud Run, etc.) Experience in Cloud platforms - GCP Python, PySpark, Project & resource management SVN, JIRA, Automation workflow (Composer, Cloud Scheduler, Apache Airflow, Tidal, Tivoli or similar) Good to have Skills: UNIX shell scripting, SnowFlake, Redshift, Familiar with NoSQL such as MongoDB, etc ETL tool (Databricks / AWS Glue / AWS Lambda / Amazon Kinesis / Amazon Firehose / Azure Data Factory / ADF / DBT / Talend, Informatica, IICS (Informatica cloud) ) Experience in Cloud platforms - AWS / Azure Client-facing skills Key Responsibilities: Ability to design simple to medium data solutions for clients by using cloud architecture using GCP Strong understanding of DW, data mart, data modeling, data structures, databases, and data ingestion and transformation. Working knowledge of ETL as well as database skills Working knowledge of data modeling, data structures, databases, and ETL processes Strong understanding of relational and non-relational databases and when to use them Leadership and communication skills to collaborate with local leadership as well as our global teams Translating technical requirements into ETL/ SQL application code Document project architecture, explain the detailed design to the team, and create low-level to high-level design Create technical documents for ETL and SQL developments using Visio, PowerPoint, and other MS Office package Will need to engage with Project Managers, Business Analysts, and Application DBA to implement ETL Solutions Perform mid to complex-level tasks independently Support Clients, Data Scientists, and Analytical Consultants working on marketing solution Work with cross-functional internal teams and external clients Strong project management and organization skills . Ability to lead 1 – 2 projects of team size 2 – 3 team members. Code management systems which include Code review, deployment, cod Work closely with the QA / Testing team to help identify/implement defect reduction initiatives Work closely with the Architecture team to make sure Architecture standards and principles are followed during development Performing Proof of Concepts on new platforms/validating proposed solutions Work with the team to establish and reinforce disciplined software development, processes, standards, and error recovery procedures are deployed Must understand software development methodologies including waterfall and agile Distribute and manage SQL development Work across the team The candidate must be willing to work during overlapping hours with US-based teams to ensure effective collaboration and communication, typically between [e.g., 6:00 PM to 11:00 PM IST], depending on project needs. Qualifications: Bachelor’s or Master's Degree in Computer Science with >= 7 years of IT experience Location: Bangalore Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less

The Technical Lead / Technical Consultant is a core role and focal point of the project team responsible for the whole technical solution and managing the day-to-day delivery. The role will focus on the technical solution architecture, detailed technical design, coaching of the development/implementation team, and governance of the technical delivery. Technical ownership of the solution from bid inception through implementation to client delivery, followed by after-sales support and best practice advice. Interactions with internal stakeholders and clients to explain technology solutions and a clear understanding of client’s business requirements through which to guide optimal design to meet their needs. Job Description: Must-Have Skills: Database (one or more of MS SQL Server, Oracle, Cloud SQL, Cloud Spanner, etc.) Data Warehouse (one or more of Big Query, SnowFlake, etc.) ETL tool (two or more of Cloud Data Fusion, Dataflow, Dataproc, Pub/Sub, Composer, Cloud Functions, Cloud Run, etc.) Experience in Cloud platforms - GCP Python, PySpark, Project & resource management SVN, JIRA, Automation workflow (Composer, Cloud Scheduler, Apache Airflow, Tidal, Tivoli or similar) Good to have Skills: UNIX shell scripting, SnowFlake, Redshift, Familiar with NoSQL such as MongoDB, etc ETL tool (Databricks / AWS Glue / AWS Lambda / Amazon Kinesis / Amazon Firehose / Azure Data Factory / ADF / DBT / Talend, Informatica, IICS (Informatica cloud) ) Experience in Cloud platforms - AWS / Azure Client-facing skills Key Responsibilities: Ability to design simple to medium data solutions for clients by using cloud architecture using GCP Strong understanding of DW, data mart, data modeling, data structures, databases, and data ingestion and transformation. Working knowledge of ETL as well as database skills Working knowledge of data modeling, data structures, databases, and ETL processes Strong understanding of relational and non-relational databases and when to use them Leadership and communication skills to collaborate with local leadership as well as our global teams Translating technical requirements into ETL/ SQL application code Document project architecture, explain the detailed design to the team, and create low-level to high-level design Create technical documents for ETL and SQL developments using Visio, PowerPoint, and other MS Office package Will need to engage with Project Managers, Business Analysts, and Application DBA to implement ETL Solutions Perform mid to complex-level tasks independently Support Clients, Data Scientists, and Analytical Consultants working on marketing solution Work with cross-functional internal teams and external clients Strong project management and organization skills . Ability to lead 1 – 2 projects of team size 2 – 3 team members. Code management systems which include Code review, deployment, cod Work closely with the QA / Testing team to help identify/implement defect reduction initiatives Work closely with the Architecture team to make sure Architecture standards and principles are followed during development Performing Proof of Concepts on new platforms/validating proposed solutions Work with the team to establish and reinforce disciplined software development, processes, standards, and error recovery procedures are deployed Must understand software development methodologies including waterfall and agile Distribute and manage SQL development Work across the team The candidate must be willing to work during overlapping hours with US-based teams to ensure effective collaboration and communication, typically between [e.g., 6:00 PM to 11:00 PM IST], depending on project needs. Qualifications: Bachelor’s or Master's Degree in Computer Science with >= 7 years of IT experience Location: Bangalore Brand: Merkle Time Type: Full time Contract Type: Permanent Show more Show less