100 Aws Redshift Jobs

As a DataBricks Developer at Astellas Pharma Inc., based in Bangalore, India, you will play a crucial role in managing the commercial integration backlog and development team for the Commercial (GrowthX) Data Integration service. Your responsibilities will include: - Designing and building scalable data pipelines using DataBricks. - Collaborating with data modelers to create efficient data structures. - Developing and maintaining Python scripts for data processing and transformation. - Working with Azure and AWS services for data storage and processing. - Contributing to the optimization of data workflows and ETL processes. In addition to the essential job responsibilities, you will also be involved in the following areas: End-to-End Data Solutions: - Supporting the design of end-to-end data streams, storage, data serving systems, and analytical workflows. - Defining overall architecture, capabilities, platforms, tools, and governing processes. Data Pipeline Development: - Building data pipelines to extract, transform, and load data from various sources. - Setting up metadata and master data structures to support transformation pipelines in Databricks. Data Modelling: - Collaborating with key stakeholders to create efficient data models and data structures in the DataBricks environment. Data Warehousing and Data Lakes: - Supporting the creation of data warehouses and data lakes for efficient data storage and management. - Developing and deploying data processing and analytics tools. In this role, you are required to have: - Bachelor's degree in computer science, Information Technology, or related field (Masters preferred) or equivalent experience. - Relevant cloud-based DataBricks, AWS, or Azure certifications. - Experience using ETL tools like Talend / Talend Cloud and DataStage. - Knowledge and experience using Azure DevOps. - Experience in working with MPP Databases like AWS Redshift. - Experience of delivering architectural solutions effectively within Lifesciences or Pharma Domains. Preferred qualifications include: - Experience analyzing and building star schema data warehouses. - Experience writing SQL and creating stored procedures. - Data Analysis and Automation Skills. - Agile Champion with proven track record in CI/CD pipelines for continuous delivery. Please note that Astellas Pharma Inc. is committed to equality of opportunity in all aspects of employment.,

Role Overview: You will be responsible for architecting and delivering highly scalable, distributed, cloud-based enterprise data solutions. Your role will involve designing scalable data architectures with Snowflake, integrating cloud technologies such as AWS, Azure, GCP, and ETL/ELT tools like DBT. Additionally, you will guide teams in proper data modeling, transformation, security, and performance optimization. Key Responsibilities: - Architect and deliver highly scalable, distributed, cloud-based enterprise data solutions - Design scalable data architectures with Snowflake and integrate cloud technologies like AWS, Azure, GCP, and ETL/ELT tools such as DBT - Guide teams in proper data modeling (star, snowflake schemas), transformation, security, and performance optimization - Load data from disparate data sets and translate complex functional and technical requirements into detailed design - Deploy Snowflake features such as data sharing, events, and lake-house patterns - Implement data security and data access controls and design - Understand relational and NoSQL data stores, methods, and approaches (star and snowflake, dimensional modeling) - Utilize AWS, Azure, or GCP data storage and management technologies such as S3, Blob/ADLS, and Google Cloud Storage - Implement Lambda and Kappa Architectures - Utilize Big Data frameworks and related technologies, with mandatory experience in Hadoop and Spark - Utilize AWS compute services like AWS EMR, Glue, and Sagemaker, as well as storage services like S3, Redshift, and DynamoDB - Experience with AWS Streaming Services like AWS Kinesis, AWS SQS, and AWS MSK - Troubleshoot and perform performance tuning in Spark framework - Spark core, SQL, and Spark Streaming - Experience with flow tools like Airflow, Nifi, or Luigi - Knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build, and Code Commit - Experience with AWS CloudWatch, AWS Cloud Trail, AWS Account Config, AWS Config Rules Qualifications Required: - 8-12 years of relevant experience - Hands-on experience with Snowflake utilities, SnowSQL, SnowPipe, ETL data Pipelines, Big Data model techniques using Python/Java - Strong expertise in the end-to-end implementation of Cloud data engineering solutions like Enterprise Data Lake, Data hub in AWS - Proficiency in AWS, Data bricks, and Snowflake data warehousing, including SQL, Snow pipe - Experience in data security, data access controls, and design - Strong AWS hands-on expertise with a programming background preferably Python/Scala - Good knowledge of Big Data frameworks and related technologies, with mandatory experience in Hadoop and Spark - Good experience with AWS compute services like AWS EMR, Glue, and Sagemaker and storage services like S3, Redshift & Dynamodb - Experience with AWS Streaming Services like AWS Kinesis, AWS SQS, and AWS MSK - Troubleshooting and Performance tuning experience in Spark framework - Spark core, SQL, and Spark Streaming - Experience in one of the flow tools like Airflow, Nifi, or Luigi - Good knowledge of Application DevOps tools (Git, CI/CD Frameworks) - Experience in Jenkins or Gitlab with rich experience in source code management like Code Pipeline, Code Build, and Code Commit - Experience with AWS CloudWatch, AWS Cloud Trail, AWS Account Config, AWS Config Rules Kindly share your profiles on dhamma.b.bhawsagar@pwc.com if you are interested in this opportunity.,

At Rearc, we are dedicated to empowering engineers like you to create exceptional products and experiences by providing you with the best tools possible. We value individuals who think freely, challenge the norm, and embrace alternative problem-solving approaches. If you are driven by the desire to make a difference and solve complex problems, you'll feel right at home with us. As a Data Engineer at Rearc, you will be an integral part of our data engineering team, contributing to the optimization of data workflows for efficiency, scalability, and reliability. Your role will involve designing and implementing robust data solutions in collaboration with cross-functional teams to meet business objectives and uphold data management best practices. **Key Responsibilities:** - **Collaborate with Colleagues:** Work closely with team members to understand customers" data requirements and contribute to developing tailored data solutions. - **Apply DataOps Principles:** Utilize modern data engineering tools like Apache Airflow and Apache Spark to create scalable data pipelines and architectures. - **Support Data Engineering Projects:** Assist in managing and executing data engineering projects, providing technical support and ensuring project success. - **Promote Knowledge Sharing:** Contribute to the knowledge base through technical blogs and articles, advocating for best practices in data engineering and fostering a culture of continuous learning and innovation. **Qualifications Required:** - 2+ years of experience in data engineering, data architecture, or related fields. - Proven track record in contributing to complex data engineering projects and implementing scalable data solutions. - Hands-on experience with ETL processes, data warehousing, and data modeling tools. - Understanding of data integration tools and best practices. - Familiarity with cloud-based data services and technologies such as AWS Redshift, Azure Synapse Analytics, Google BigQuery. - Strong analytical skills for data-driven decision-making. - Proficiency in implementing and optimizing data pipelines using modern tools and frameworks. - Excellent communication and interpersonal skills for effective collaboration with teams and stakeholders. Your journey at Rearc will begin with an immersive learning experience to help you get acquainted with our processes. In the initial months, you will have the opportunity to explore various tools and technologies as you find your place within our team.,

As a DataBricks Developer at Astellas Pharma Inc., you will play a crucial role in managing the commercial integration backlog and development team by assisting in designing and building scalable data pipelines using DataBricks. Your responsibilities will include: - Collaborating with data modelers to create efficient data structures. - Developing and maintaining Python scripts for data processing and transformation. - Working with Azure and AWS services for data storage and processing. - Contributing to the optimization of data workflows and ETL processes. In addition to the above, you will also be involved in the following areas: End-to-End Data Solutions: - Supporting the design of end-to-end data streams, storage, data serving systems, and analytical workflows. - Defining overall architecture, capabilities, platforms, tools, and governing processes. Data Pipeline Development: - Building data pipelines to extract, transform, and load data from various sources. - Setting up metadata and master data structures to support transformation pipelines in Databricks. Data Modelling: - Collaborating with key stakeholders to create efficient data models and data structures in the DataBricks environment. Data Warehousing and Data Lakes: - Supporting the creation of data warehouses and data lakes for efficient data storage and management. - Developing and deploying data processing and analytics tools. Continuous Learning: - Staying up to date on the latest data technologies, trends, and best practices. - Participating in smaller focused mission teams to deliver value-driven solutions aligned with global initiatives. Qualifications: Required - Bachelor's degree in computer science, Information Technology, or related field (Masters preferred) or equivalent experience. - Any relevant cloud-based DataBricks, AWS, or Azure certifications. - Experience using ETL tools like Talend / Talend Cloud and DataStage. - Knowledge and experience using Azure DevOps. - Experience working with MPP Databases like AWS Redshift. Preferred - Experience analyzing and building star schema data warehouses. - Experience writing SQL and creating stored procedures. - Proficient in identifying, standardizing, and automating critical reporting metrics and modeling tools. - Experience in integrating data from multiple sources like relational databases, Salesforce, SAP, and API calls. By leveraging your knowledge of Machine Learning (ML) and data engineering principles, you will integrate with existing data pipelines and explore new possibilities for data utilization. Stay updated on the latest trends in full-stack development, data engineering, and cloud platforms to excel in this role at Astellas Pharma Inc.,

Job Description: WNS (Holdings) Limited is a leading Business Process Management (BPM) company that collaborates with clients across various industries to create innovative digital transformation solutions. As a Data Analyst in WNS, your key responsibilities will include building visualizations using tools like Tableau, analyzing complex data sets to identify trends and insights, writing efficient SQL queries, creating interactive visualizations, collaborating with teams to understand business requirements, maintaining data pipelines, and effectively communicating data findings to stakeholders. You should have at least 5 years of experience in data analysis, hands-on experience with SQL programming, and knowledge of AWS Redshift or similar database technologies. Familiarity with R or Python is a plus but not mandatory. Strong communication skills and business analysis acumen are essential for this role. This position requires a Graduate or Post Graduate degree. Join WNS to be part of a dynamic team that co-creates and executes digital transformation visions for numerous clients with operational excellence.,

NTT DATA is looking for a Software Dev. Sr. Specialist Advisor to join the team in Noida, Uttar Pradesh, India. As an AWS Redshift Datalake engineer, you will work with the Data team to create and maintain scalable data pipelines dealing with petabytes of data. The projects involve cutting-edge technologies, petabyte-scale data processing systems, data warehouses, and data lakes to meet the growing information needs of customers. You should have 5+ years of hands-on experience in AWS Redshift, including data loading into Redshift and ETL experience. Additionally, you should be proficient in data modeling, SQL stored procedures, basic Python, and JSON files manipulation. Experience working in agile teams is required. Nice to have skills include Airflow, Kafka, and Tableau. Your responsibilities will include participating in daily scrum meetings, design and development activities, providing expert advice to resolve technical bottlenecks, implementing POCs to address technical debts, and mentoring the team to enhance AWS knowledge. The ideal candidate will have a Bachelor of Engineering/Technology degree with a focus on Computer Science or Software Engineering (or equivalent). NTT DATA is a trusted global innovator of business and technology services, serving 75% of the Fortune Global 100. With experts in over 50 countries and a robust partner ecosystem, NTT DATA offers consulting, data and artificial intelligence, industry solutions, application development, infrastructure management, and more. As a part of the NTT Group, NTT DATA invests significantly in R&D to support organizations and society in the digital future. Visit us at us.nttdata.com.,

As a DevOps Pipeline Optimization Specialist (ETL) in our team, you will be responsible for optimizing and enhancing ETL pipelines within a DataLake application environment. Your role will involve identifying and resolving bottlenecks in managing multiple ETL instances, optimizing runtime and resource consumption, and ensuring seamless integration and regression testing. You will analyze the existing DevOps pipeline to identify areas for performance improvement, optimize ETL pipeline execution, and refactor and enhance existing code to improve efficiency. Collaboration with ETL teams for regression testing and validation, addressing data validation and optimization issues, preparing technical documentation, and providing post-deployment support to ensure pipeline stability will also be part of your responsibilities. Key Responsibilities: - Collaborate with development and support teams to understand the ETL pipeline flow and optimize workflow execution, scheduling, and resource utilization. - Refactor and enhance ETL code to improve performance, prepare test datasets, and conduct testing to ensure responsiveness, efficiency, and scalability. - Identify and resolve VA (Validation & Authentication) issues in the ETL pipeline, maintain technical documentation, and process flow diagrams. - Work closely with DevOps, Data Engineers, and Cloud teams to implement optimizations and provide post-deployment support to monitor pipeline performance. Required Skills & Experience: - 5+ years of hands-on experience in ETL development, optimization, and DevOps pipeline management. - Strong Python, PySpark, and Spark programming skills. - Experience with AWS Cloud technologies such as Athena, S3, Lambda, EMR, Airflow, Glue, RDS, and DMS. - Expertise in Data Warehousing, AWS Redshift, and RDS Postgres. - Strong background in ETL pipeline development, debugging, and optimization. - Experience in CI/CD, automation, and DevOps practices. - Excellent problem-solving, analytical, and debugging skills. - Ability to work in hybrid environments (on-prem & cloud-based) and collaborate effectively with cross-functional teams. Preferred Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering, or related field. - Experience with Terraform, Kubernetes, or Docker for cloud-based deployments. - Familiarity with streaming data solutions such as Kafka, Kinesis, or similar. - Knowledge of machine learning pipelines in AWS is a plus. Join us to work on cutting-edge ETL pipeline optimization projects in a high-scale DataLake environment with a hybrid work model offering flexibility across Chennai, Hyderabad, and Bangalore. You will have career growth opportunities in Data Engineering, DevOps, and AWS Cloud, and experience a collaborative and innovative work culture with exposure to the latest cloud technologies. Notice Period: Immediate to 30 days preferred. Job Types: Full-time, Permanent Benefits: Health insurance, Paid sick time, Provident Fund Schedule: Day shift, Monday to Friday, Morning shift, Performance bonus Application Question: What is the notice period in days Education: Bachelor's (Required) Work Location: In person,

As a Data Engineer, you will be responsible for designing, developing, and optimizing data pipelines and ETL workflows using AWS Glue, AWS Lambda, and Apache Spark. Your role will involve implementing big data processing solutions utilizing AWS EMR and AWS Redshift. You will also be tasked with developing and maintaining data lakes and data warehouses on AWS, including S3, Redshift, and RDS. Ensuring data quality, integrity, and governance will be a key aspect of your responsibilities, which will be achieved through leveraging AWS Glue Data Catalog and AWS Lake Formation. It will be essential for you to optimize data storage and processing for both performance and cost efficiency. Working with structured, semi-structured, and unstructured data across various storage formats such as Parquet, Avro, and JSON will be part of your daily tasks. Automation and orchestration of data workflows using AWS Step Functions and Apache Airflow will also fall within your scope of work. You will be expected to implement best practices for CI/CD pipelines in data engineering with AWS CodePipeline and AWS CodeBuild. Monitoring, troubleshooting, and optimizing data pipeline performance and scalability will be critical to ensuring smooth operations. Collaborating with cross-functional teams, including data scientists, analysts, and software engineers, will be necessary to drive successful outcomes. Your role will require a minimum of 6 years of experience in data engineering and big data processing. Proficiency in AWS cloud services like AWS Glue, AWS Lambda, AWS Redshift, AWS EMR, and S3 is paramount. Strong skills in Python for data engineering tasks, hands-on experience with Apache Spark and SQL, as well as knowledge of data modeling, schema design, and performance tuning are essential. Understanding AWS Lake Formation and Lakehouse principles, experience with version control using Git, and familiarity with CI/CD pipelines are also required. Knowledge of data security, compliance, and governance best practices is crucial. Experience with real-time streaming technologies such as Kafka and Kinesis will be an added advantage. Strong problem-solving, analytical, and communication skills are key attributes for success in this role.,

You will be joining Accordion, working at the intersection of sponsors and management teams to provide hands-on, execution-focused support for enhancing the capabilities of the CFO's office. Working at Accordion means being part of a team of 1,000+ analytics, finance, and technology experts in a high-growth, agile, and entrepreneurial environment. You will play a significant role in changing the way portfolio companies drive value and contribute to Accordions future by embracing a culture rooted in collaboration and a commitment to building something great together. As part of Accordion's Data & Analytics (D&A) team, you will offer cutting-edge, intelligent solutions to a global clientele by leveraging domain knowledge, sophisticated technology tools, and deep analytics capabilities. Collaborating with Private Equity clients and their Portfolio Companies across various sectors, including Retail, CPG, Healthcare, Media & Entertainment, Technology, and Logistics, you will deliver data and analytical solutions designed to streamline reporting capabilities and enhance business insights across complex data sets. In the role of Technical Director at Accordion, you will be responsible for designing, developing, configuring/deploying, and maintaining the technology stack related to data and analytics. You must have an in-depth understanding of various tools and technologies in the domain to design and implement robust and scalable solutions that address client requirements effectively. Evaluating existing architectures and recommending upgrades and improvements, both on-premises and cloud-based solutions, will be a key aspect of your role. The ideal candidate for this role will have an undergraduate degree from tier-1/tier-2 colleges, more than 7 years of experience in the field, proven expertise in SQL Server, in-depth knowledge of databases and data warehousing, familiarity with business intelligence tools, and a good understanding of cloud platforms like Azure or AWS. Strong organizational, critical thinking, and communication skills are also essential for success in this position. As a Technical Director at Accordion, you will work closely with business and technology teams to guide solution development and implementation, develop standard reports and functional dashboards, conduct training programs for junior developers, recommend improvements for reporting solutions, and create an end-to-end Business Intelligence framework based on client requirements. Your role will involve partnering with clients to understand their business and create comprehensive business requirements, as well as recommending appropriate architecture, analytics, and reporting solutions based on those requirements.,

As a Data Warehousing Developer at our client, a global leader in energy management and automation, your primary responsibility will be to design, develop, and deliver ETL solutions on the corporate Data Platform. You will not only work on solutions for yourself but also lead a team of developers working on specific projects. In this role, you will be utilizing your expertise in AWS Redshift and Informatica ETL to ensure successful technology and solution delivery. Your key responsibilities will include leading and guiding an Informatica-based ETL architecture to handle complex business rules while meeting stringent performance requirements. You will drive the design and determine the ETL requirements for BI projects, partnering with ETL developers to develop error handling processes and load dimensional star schemas. Furthermore, you will play an active role in shaping and enhancing the overall ETL Informatica architecture, including defining standards, patterns, and best practices. Collaborating with the Data architect, you will work towards improving the current data landscape and future strategy. Additionally, you will partner with the Leadership team to ensure the successful delivery of projects. To excel in this role, you should have at least 5 years of hands-on experience in Informatica PWC ETL development, 7 years of experience in SQL, analytical data modeling (STAR schema), and Informatica PowerCenter, as well as 5 years of experience with Redshift, Oracle, or comparable databases in BI/DW deployments. Familiarity with AWS Services and proven experience with STAR and SNOWFLAKE schema techniques will be beneficial. You will also be responsible for staying updated on new ETL techniques and methodologies, communicating trends and opportunities to management and other developers, and identifying opportunities for technology enhancements aligned with business goals. Mentoring team members and providing technical assistance, troubleshooting, and alternative development solutions will be key aspects of this role. Overall, as a Data Warehousing Developer, you will play a critical role in driving the success of ETL solutions within the organization, contributing to the optimization and scalability of data platforms, and ensuring alignment with enterprise architecture and business objectives.,

As an experienced candidate with 5-8 years of relevant experience, you will be expected to have proficiency in Informatica PWC skills. Additionally, hands-on experience with AWS Redshift and S3 is essential for this role. Your responsibilities will include SQL scripting and familiarity with Redshift commands to effectively contribute to the team's success.,

As an experienced BI Developer with a strong expertise in SSIS (SQL Server Integration Services) and SSAS (SQL Server Analysis Services), you will be responsible for developing, implementing, and optimizing Business Intelligence solutions for our clients. Your role will involve contributing to data integration, analysis, and reporting requirements. You must have a deep understanding of database management, data warehousing concepts, and hands-on experience with the Microsoft BI Stack. You should have at least 7+ years of hands-on experience in BI development with a focus on SSIS and SSAS. Familiarity with all aspects of SDLC is essential. Detailed experience with SQL Server, Analysis Services, Integration Services, Reporting Services (SSRS and PowerBI), and MDX queries for Cubes is required. Experience in SSAS multi-cube and excellent system design skills in SQL Server Business Intelligence are also necessary. Additionally, experience with Source control GIT, Jenkins, and knowledge of Banking, Markets/Treasury products are highly desirable. It would be nice to have experience with other BI tools such as Power BI or Tableau, knowledge of data warehousing concepts and technologies (e.g., Azure Data Factory, Snowflake, or Google BigQuery), familiarity with Agile methodologies and DevOps practices for CI/CD in BI development, knowledge of MDX and DAX, experience in automating and scheduling jobs using SQL Server Agent or third-party tools, exposure to cloud-based BI solutions like Azure Synapse Analytics or AWS Redshift, and an understanding of financial data and reporting requirements. Your responsibilities will include providing technical expertise to the team, delivering results based on requirements set by the team lead, providing oversight for the quality of the application and artifacts related to the application analysis and development, collaborating with the production support team to implement sound change planning and change management, being proactive in uncovering risk and managing issues, striving for best practices in design and development, and contributing to the technology strategic agenda by driving application architecture simplicity and minimizing production incidents through high-quality development and processes.,

As a Data Analyst at iCubes in Udaipur, you will be part of a dynamic team that is focused on transforming data into actionable insights to drive business strategies and enhance operational efficiency. Your role will involve working with marketing tools such as Google Analytics, Facebook Ads, and Google Ads, as well as analyzing Sales & Marketing data to provide valuable recommendations and support decision-making processes. Requirements: - Minimum 2 years of experience as a Data Analyst - Proficiency in working with Sales & Marketing data - Ability to work independently and collaboratively in a fast-paced team environment - Bachelor's degree in Data Science, Statistics, Computer Science, or a related field - Strong problem-solving skills and attention to detail - Experience with large datasets and database systems - Advanced Excel skills, including pivot tables and complex formulas - Proficiency in data analysis tools such as SQL, Python, or R, and data visualization tools like Tableau, Power BI, Looker Studio - Familiarity with cloud-based data solutions like AWS Redshift, Google BigQuery is an advantage - Understanding of statistical methods and data modeling techniques - Knowledge of data mining, statistical analysis, and data visualization Responsibilities: - Design and implement data collection processes - Extract data from primary and secondary sources and ensure data integrity - Automate data extraction and transformation processes for streamlined workflows - Create interactive data visualizations and dashboards to communicate findings effectively - Collaborate with stakeholders to understand requirements and provide actionable analytics solutions - Perform exploratory data analysis to identify trends and patterns - Conduct statistical analysis and modeling to support decision-making - Provide recommendations based on data analysis to enhance business strategies - Stay updated on the latest technologies and best practices in data analysis If you are passionate about data and eager to contribute high-quality analysis and reporting to our organization, we invite you to apply for this exciting opportunity at iCubes. Join our team and be a part of our success by leveraging data assets effectively. Visit our website for more information about our services and team. Apply now and be a valuable member of our data-driven team!,

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant-Data Engineer, AWS+Python, Spark, Kafka for ETL! Responsibilities Develop, deploy, and manage ETL pipelines using AWS services, Python, Spark, and Kafka. Integrate structured and unstructured data from various data sources into data lakes and data warehouses. Design and deploy scalable, highly available, and fault-tolerant AWS data processes using AWS data services (Glue, Lambda, Step, Redshift) Monitor and optimize the performance of cloud resources to ensure efficient utilization and cost-effectiveness. Implement and maintain security measures to protect data and systems within the AWS environment, including IAM policies, security groups, and encryption mechanisms. Migrate the application data from legacy databases to Cloud based solutions (Redshift, DynamoDB, etc) for high availability with low cost Develop application programs using Big Data technologies like Apache Hadoop, Apache Spark, etc with appropriate cloud-based services like Amazon AWS, etc. Build data pipelines by building ETL processes (Extract-Transform-Load) Implement backup, disaster recovery, and business continuity strategies for cloud-based applications and data. Responsible for analysing business and functional requirements which involves a review of existing system configurations and operating methodologies as well as understanding evolving business needs Analyse requirements/User stories at the business meetings and strategize the impact of requirements on different platforms/applications, convert the business requirements into technical requirements Participating in design reviews to provide input on functional requirements, product designs, schedules and/or potential problems Understand current application infrastructure and suggest Cloud based solutions which reduces operational cost, requires minimal maintenance but provides high availability with improved security Perform unit testing on the modified software to ensure that the new functionality is working as expected while existing functionalities continue to work in the same way Coordinate with release management, other supporting teams to deploy changes in production environment Qualifications we seek in you! Minimum Qualifications Experience in designing, implementing data pipelines, build data applications, data migration on AWS Strong experience of implementing data lake using AWS services like Glue, Lambda, Step, Redshift Experience of Databricks will be added advantage Strong experience in Python and SQL Proven expertise in AWS services such as S3, Lambda, Glue, EMR, and Redshift. Advanced programming skills in Python for data processing and automation. Hands-on experience with Apache Spark for large-scale data processing. Experience with Apache Kafka for real-time data streaming and event processing. Proficiency in SQL for data querying and transformation. Strong understanding of security principles and best practices for cloud-based environments. Experience with monitoring tools and implementing proactive measures to ensure system availability and performance. Excellent problem-solving skills and ability to troubleshoot complex issues in a distributed, cloud-based environment. Strong communication and collaboration skills to work effectively with cross-functional teams. Preferred Qualifications/ Skills Master’s Degree-Computer Science, Electronics, Electrical. AWS Data Engineering & Cloud certifications, Databricks certifications Experience with multiple data integration technologies and cloud platforms Knowledge of Change & Incident Management process Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

As a Senior Data Engineer at Career Mantra, you will be responsible for designing, developing, and maintaining scalable data pipelines while optimizing data storage solutions. Your role will involve working with cloud platforms, big data technologies, and ETL processes to support business intelligence and analytics. Key Responsibilities: - Design and implement scalable data pipelines using Python, PySpark, and Big Data tools. - Optimize data processing performance in AWS. - Collaborate with business teams to deliver reliable data solutions. - Develop and maintain ETL processes using tools like Airflow, Azkaban, and AWS Glue. - Troubleshoot and ensure data integrity across data pipelines. - Mentor junior team members and promote best practices. Key Skills: - Strong experience with Python, PySpark, SQL, AWS (Redshift, Glue, S3). - Expertise in big data technologies (Hadoop, Hive, Spark). - Proficient in data modeling and ETL orchestration. - Experience with business intelligence tools (Tableau, Power BI). - Strong problem-solving and communication skills. Qualifications And Skills: - Extensive experience with data mapping for accurate data translation and transformation across systems. - Proficient in ETL processes for efficient extraction, transformation, and loading of data. - Strong knowledge of API Integration for smooth communication between different software solutions. - Expertise in System Integration to ensure harmonious operation of various IT systems and platforms. - Experience with Middleware Technologies to facilitate connectivity and collaboration between applications. - Competency in Scripting Languages for automating routine processes and enhancing system functions. - Proven Database Management skills to ensure data integrity and performance optimization. - Adept at Troubleshooting to identify, diagnose, and resolve technical issues promptly. Roles And Responsibilities: - Design and implement solutions for complex data integration projects to enhance operational efficiency. - Collaborate with cross-functional teams to ensure smooth integration and alignment of IT systems. - Develop and execute testing plans to verify the functionality and performance of integrated systems. - Monitor system performance and suggest necessary improvements for optimal operation and stability. - Serve as a technical expert, providing guidance and support to junior team members and stakeholders. - Maintain comprehensive documentation of integration processes, configurations, and best practices. - Stay current with technology trends and advancements to incorporate industry best practices. - Ensure compliance with company policies and standards in all integration activities.,

As a Data Architect, your primary responsibility is to design and manage scalable, secure, and high-performance data architectures that cater to the needs of GEDU and its customers. You will play a crucial role in ensuring that data assets within GEDU are well-structured and managed to facilitate insightful decision-making, data integrity, and aligned with strategic goals. Your key responsibilities will include designing, developing, and maintaining enterprise data architecture, which encompasses data models, database schemas, and data flow diagrams. You will also be tasked with developing a data strategy and roadmap that aligns with GEDU's business objectives while ensuring scalability. Architecting both transactional (OLTP) and analytical (OLAP) databases to guarantee optimal performance and data consistency will also be part of your role. Moreover, you will oversee the integration of disparate data sources into a unified data platform by leveraging ETL/ELT processes and data integration tools. Designing and implementing data warehousing solutions, data lakes, and data marts that enable efficient storage and retrieval of large datasets will also be a critical aspect of your responsibilities. Ensuring proper data governance, including data ownership, security, and privacy controls in compliance with standards like GDPR and HIPAA, will be essential. Collaborating closely with business stakeholders, analysts, developers, and executives to understand data requirements and ensure that the architecture supports analytics and reporting needs will be crucial. You will also collaborate with DevOps and engineering teams to optimize database performance and support large-scale data processing pipelines. Guiding the selection of data technologies such as databases (SQL/NoSQL), data processing frameworks (Hadoop, Spark), cloud platforms (Azure), and analytics tools will be part of your role. Staying updated on emerging data management technologies, trends, and best practices and assessing their potential application within the organization will also be essential. You will be responsible for defining data quality standards and implementing processes to ensure accuracy, completeness, and consistency of data across all systems. Establishing protocols for data security, encryption, backup/recovery to protect data assets, and ensure business continuity will be vital. Additionally, you will lead and mentor data engineers, data modelers, and other technical staff in best practices for data architecture and management. Providing strategic guidance on data-related projects and initiatives to ensure alignment with the enterprise data strategy will also be part of your responsibilities. With over 7 years of experience in data architecture, data modeling, and database management, you should possess proficiency in designing and implementing relational (SQL) and non-relational (NoSQL) database solutions. Strong experience with data integration tools (Azure Tools are a must), ETL/ELT processes, and data pipelines will be required. Expertise in Azure cloud data platform is a must, with additional experience in platforms like AWS (Redshift, S3), Azure (Data Lake, Synapse), Google Cloud Platform (BigQuery, Dataproc) being a bonus. Hands-on experience with big data technologies (Hadoop, Spark), distributed systems for large-scale data processing, data warehousing solutions, and BI tools (Power BI, Tableau, Looker) will also be beneficial. Your technical leadership skills should enable you to lead data-driven projects, manage stakeholders effectively, and drive data strategies across the enterprise. Strong programming skills in languages like Python, SQL, R, or Scala will also be necessary for this role. Finally, your pre-sales responsibilities will involve stakeholder engagement, solution development, developing proof of concepts (POCs), client communication, and delivering technical presentations to prospective clients. Ensuring that solutions align with business objectives, meet security and performance benchmarks, and effectively communicate technical requirements to clients and stakeholders will be crucial in the pre-sales process.,

You are seeking a Head of Architecture role that involves defining and driving the end-to-end architecture strategy for REA India, a leading real estate technology platform in India. As the Head of Architecture, your primary focus will be on scalability, security, cloud optimization, and AI-driven innovation. This leadership position requires mentoring teams, enhancing development efficiency, and collaborating with REA Group leaders to align with the global architectural strategy. Your key responsibilities in this role will include: - Architectural Leadership: Documenting key technical choices, implementing scalable and secure architectures across Housing and PropTiger, and aligning technical decisions with business goals using microservices, distributed systems, and API-first design. - Cloud & DevOps Excellence: Optimizing cloud infrastructure for cost, performance, and scalability, improving SEO performance, and enhancing CI/CD pipelines, automation, and Infrastructure as Code (IaC) to accelerate delivery. - Security & Compliance: Establishing and enforcing security best practices for data protection, identity management, and compliance, as well as strengthening security posture through proactive risk mitigation and governance. - Data & AI Strategy: Architecting data pipelines and AI-driven solutions for automation and data-driven decision-making, leading Generative AI initiatives to enhance product development and user experiences. - Incident Management & Operational Excellence: Establishing best practices for incident management, driving site reliability engineering (SRE) principles to improve uptime, observability, and performance monitoring. - Team Leadership & Mentorship: Mentoring engineering teams to foster a culture of technical excellence, innovation, and continuous learning, as well as collaborating with product and business leaders to align technology roadmaps with strategic objectives. The ideal candidate for this role should have: - 12+ years of experience in software architecture, cloud platforms (AWS/GCP), and large-scale system design. - Expertise in microservices, API design, DevOps, CI/CD, and cloud cost optimization. - Strong background in security best practices and governance. - Experience in Data Architecture, AI/ML pipelines, and Generative AI applications. - Proven leadership skills in mentoring and developing high-performing engineering teams. - Strong problem-solving, analytical, and cross-functional collaboration skills. By joining REA India in the Head of Architecture role, you will have the opportunity to: - Build and lead high-scale real estate tech products. - Drive cutting-edge AI and cloud innovations. - Mentor and shape the next generation of top engineering talent. In summary, as the Head of Architecture at REA India, you will play a crucial role in shaping the architecture strategy, driving innovation, and leading a team of talented individuals towards achieving the company's vision of changing the way India experiences property.,

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant-Data Engineer, AWS+Python, Spark, Kafka for ETL! Responsibilities Develop, deploy, and manage ETL pipelines using AWS services, Python, Spark, and Kafka. Integrate structured and unstructured data from various data sources into data lakes and data warehouses. Design and deploy scalable, highly available, and fault-tolerant AWS data processes using AWS data services (Glue, Lambda, Step, Redshift) Monitor and optimize the performance of cloud resources to ensure efficient utilization and cost-effectiveness. Implement and maintain security measures to protect data and systems within the AWS environment, including IAM policies, security groups, and encryption mechanisms. Migrate the application data from legacy databases to Cloud based solutions (Redshift, DynamoDB, etc) for high availability with low cost Develop application programs using Big Data technologies like Apache Hadoop, Apache Spark, etc with appropriate cloud-based services like Amazon AWS, etc. Build data pipelines by building ETL processes (Extract-Transform-Load) Implement backup, disaster recovery, and business continuity strategies for cloud-based applications and data. Responsible for analysing business and functional requirements which involves a review of existing system configurations and operating methodologies as well as understanding evolving business needs Analyse requirements/User stories at the business meetings and strategize the impact of requirements on different platforms/applications, convert the business requirements into technical requirements Participating in design reviews to provide input on functional requirements, product designs, schedules and/or potential problems Understand current application infrastructure and suggest Cloud based solutions which reduces operational cost, requires minimal maintenance but provides high availability with improved security Perform unit testing on the modified software to ensure that the new functionality is working as expected while existing functionalities continue to work in the same way Coordinate with release management, other supporting teams to deploy changes in production environment Qualifications we seek in you! Minimum Qualifications Experience in designing, implementing data pipelines, build data applications, data migration on AWS Strong experience of implementing data lake using AWS services like Glue, Lambda, Step, Redshift Experience of Databricks will be added advantage Strong experience in Python and SQL Proven expertise in AWS services such as S3, Lambda, Glue, EMR, and Redshift. Advanced programming skills in Python for data processing and automation. Hands-on experience with Apache Spark for large-scale data processing. Experience with Apache Kafka for real-time data streaming and event processing. Proficiency in SQL for data querying and transformation. Strong understanding of security principles and best practices for cloud-based environments. Experience with monitoring tools and implementing proactive measures to ensure system availability and performance. Excellent problem-solving skills and ability to troubleshoot complex issues in a distributed, cloud-based environment. Strong communication and collaboration skills to work effectively with cross-functional teams. Preferred Qualifications/ Skills Master’s Degree-Computer Science, Electronics, Electrical. AWS Data Engineering & Cloud certifications, Databricks certifications Experience with multiple data integration technologies and cloud platforms Knowledge of Change & Incident Management process Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant-Data Engineer, AWS+Python, Spark, Kafka for ETL! Responsibilities Develop, deploy, and manage ETL pipelines using AWS services, Python, Spark, and Kafka. Integrate structured and unstructured data from various data sources into data lakes and data warehouses. Design and deploy scalable, highly available, and fault-tolerant AWS data processes using AWS data services (Glue, Lambda, Step, Redshift) Monitor and optimize the performance of cloud resources to ensure efficient utilization and cost-effectiveness. Implement and maintain security measures to protect data and systems within the AWS environment, including IAM policies, security groups, and encryption mechanisms. Migrate the application data from legacy databases to Cloud based solutions (Redshift, DynamoDB, etc) for high availability with low cost Develop application programs using Big Data technologies like Apache Hadoop, Apache Spark, etc with appropriate cloud-based services like Amazon AWS, etc. Build data pipelines by building ETL processes (Extract-Transform-Load) Implement backup, disaster recovery, and business continuity strategies for cloud-based applications and data. Responsible for analysing business and functional requirements which involves a review of existing system configurations and operating methodologies as well as understanding evolving business needs Analyse requirements/User stories at the business meetings and strategize the impact of requirements on different platforms/applications, convert the business requirements into technical requirements Participating in design reviews to provide input on functional requirements, product designs, schedules and/or potential problems Understand current application infrastructure and suggest Cloud based solutions which reduces operational cost, requires minimal maintenance but provides high availability with improved security Perform unit testing on the modified software to ensure that the new functionality is working as expected while existing functionalities continue to work in the same way Coordinate with release management, other supporting teams to deploy changes in production environment Qualifications we seek in you! Minimum Qualifications Experience in designing, implementing data pipelines, build data applications, data migration on AWS Strong experience of implementing data lake using AWS services like Glue, Lambda, Step, Redshift Experience of Databricks will be added advantage Strong experience in Python and SQL Proven expertise in AWS services such as S3, Lambda, Glue, EMR, and Redshift. Advanced programming skills in Python for data processing and automation. Hands-on experience with Apache Spark for large-scale data processing. Experience with Apache Kafka for real-time data streaming and event processing. Proficiency in SQL for data querying and transformation. Strong understanding of security principles and best practices for cloud-based environments. Experience with monitoring tools and implementing proactive measures to ensure system availability and performance. Excellent problem-solving skills and ability to troubleshoot complex issues in a distributed, cloud-based environment. Strong communication and collaboration skills to work effectively with cross-functional teams. Preferred Qualifications/ Skills Master’s Degree-Computer Science, Electronics, Electrical. AWS Data Engineering & Cloud certifications, Databricks certifications Experience with multiple data integration technologies and cloud platforms Knowledge of Change & Incident Management process Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

Genpact (NYSE: G) is a global professional services and solutions firm delivering outcomes that shape the future. Our 125,000+ people across 30+ countries are driven by our innate curiosity, entrepreneurial agility, and desire to create lasting value for clients. Powered by our purpose the relentless pursuit of a world that works better for people – we serve and transform leading enterprises, including the Fortune Global 500, with our deep business and industry knowledge, digital operations services, and expertise in data, technology, and AI. Inviting applications for the role of Lead Consultant-Data Engineer, AWS+Python, Spark, Kafka for ETL! Responsibilities Develop, deploy, and manage ETL pipelines using AWS services, Python, Spark, and Kafka. Integrate structured and unstructured data from various data sources into data lakes and data warehouses. Design and deploy scalable, highly available, and fault-tolerant AWS data processes using AWS data services (Glue, Lambda, Step, Redshift) Monitor and optimize the performance of cloud resources to ensure efficient utilization and cost-effectiveness. Implement and maintain security measures to protect data and systems within the AWS environment, including IAM policies, security groups, and encryption mechanisms. Migrate the application data from legacy databases to Cloud based solutions (Redshift, DynamoDB, etc) for high availability with low cost Develop application programs using Big Data technologies like Apache Hadoop, Apache Spark, etc with appropriate cloud-based services like Amazon AWS, etc. Build data pipelines by building ETL processes (Extract-Transform-Load) Implement backup, disaster recovery, and business continuity strategies for cloud-based applications and data. Responsible for analysing business and functional requirements which involves a review of existing system configurations and operating methodologies as well as understanding evolving business needs Analyse requirements/User stories at the business meetings and strategize the impact of requirements on different platforms/applications, convert the business requirements into technical requirements Participating in design reviews to provide input on functional requirements, product designs, schedules and/or potential problems Understand current application infrastructure and suggest Cloud based solutions which reduces operational cost, requires minimal maintenance but provides high availability with improved security Perform unit testing on the modified software to ensure that the new functionality is working as expected while existing functionalities continue to work in the same way Coordinate with release management, other supporting teams to deploy changes in production environment Qualifications we seek in you! Minimum Qualifications Experience in designing, implementing data pipelines, build data applications, data migration on AWS Strong experience of implementing data lake using AWS services like Glue, Lambda, Step, Redshift Experience of Databricks will be added advantage Strong experience in Python and SQL Proven expertise in AWS services such as S3, Lambda, Glue, EMR, and Redshift. Advanced programming skills in Python for data processing and automation. Hands-on experience with Apache Spark for large-scale data processing. Experience with Apache Kafka for real-time data streaming and event processing. Proficiency in SQL for data querying and transformation. Strong understanding of security principles and best practices for cloud-based environments. Experience with monitoring tools and implementing proactive measures to ensure system availability and performance. Excellent problem-solving skills and ability to troubleshoot complex issues in a distributed, cloud-based environment. Strong communication and collaboration skills to work effectively with cross-functional teams. Preferred Qualifications/ Skills Master’s Degree-Computer Science, Electronics, Electrical. AWS Data Engineering & Cloud certifications, Databricks certifications Experience with multiple data integration technologies and cloud platforms Knowledge of Change & Incident Management process Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values diversity and inclusion, respect and integrity, customer focus, and innovation. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a 'starter kit,' paying to apply, or purchasing equipment or training.

As a Data Engineering Lead, you will be responsible for developing and implementing data engineering projects, including enterprise data hubs or Big data platforms. Your role will involve defining reference data architecture, leveraging cloud-native data platforms in AWS or Microsoft stack, and staying updated on the latest data trends like data fabric and data mesh. You will play a key role in leading the Center of Excellence (COE) and influencing client revenues through innovative data and analytics solutions. Your responsibilities will include guiding a team of data engineers, overseeing the design and deployment of data solutions, and strategizing new data services and offerings. Collaborating with client teams to understand their business challenges, you will develop tailored data solutions and lead client engagements from project initiation to deployment. Building strong relationships with key clients and stakeholders, you will also create reusable methodologies, pipelines, and models for more efficient data science projects. Your expertise in data architecture solutions, data governance, and data modeling will ensure compliance with regulatory standards and support effective data management processes. You will be proficient in various data integration tools, cloud computing platforms, programming languages, data visualization tools, and big data technologies to process and analyze large volumes of data. In addition to technical skills, you will demonstrate strong people and interpersonal skills by managing a high-performing team, fostering a culture of innovation, and collaborating with cross-functional teams. Candidates for this role should have at least 10+ years of experience in information technology, with a focus on data engineering and architecture, along with a degree in relevant fields like computer science, data science, or engineering. Candidates should also possess experience in managing data projects, creating data and analytics solutions, and have a good understanding of data visualization, reporting tools, and normalizing data as per key KPIs and metrics. Strong problem-solving, communication, and collaboration skills are essential for success in this role.,

We are searching for a highly skilled and seasoned Senior ETL & Data Streaming Engineer with over 10 years of experience to take on a crucial role in the design, development, and maintenance of our robust data pipelines. The ideal candidate will possess in-depth expertise in batch ETL processes as well as real-time data streaming technologies, along with extensive hands-on experience with AWS data services. A proven track record of working with Data Lake architectures and traditional Data Warehousing environments is a must. Your responsibilities will include designing, developing, and implementing highly scalable, fault-tolerant, and performant ETL processes using leading ETL tools to extract, transform, and load data from diverse source systems into our Data Lake and Data Warehouse. You will also be tasked with architecting and constructing batch and real-time data streaming solutions using technologies like Talend, Informatica, Apache Kafka, or AWS Kinesis to facilitate immediate data ingestion and processing requirements. Furthermore, you will need to leverage and optimize various AWS data services such as AWS S3, AWS Glue, AWS Redshift, AWS Lake Formation, AWS EMR, and others to develop and manage data pipelines. Collaboration with data architects, data scientists, and business stakeholders to comprehend data requirements and translate them into efficient data pipeline solutions is a key aspect of the role. It will also be essential for you to ensure data quality, integrity, and security across all data pipelines and storage solutions, as well as monitor, troubleshoot, and optimize existing data pipelines for performance, cost-efficiency, and reliability. Additionally, you will be responsible for developing and maintaining comprehensive documentation for all ETL and streaming processes, data flows, and architectural designs, and implementing data governance policies and best practices within the Data Lake and Data Warehouse environments. As a mentor to junior engineers, you will contribute to fostering a culture of technical excellence and continuous improvement. Staying updated on emerging technologies and industry best practices in data engineering, ETL, and streaming will also be expected. Required Qualifications: - 10+ years of progressive experience in data engineering, focusing on ETL, ELT, and data pipeline development. - Extensive hands-on experience with commercial or open-source ETL tools (Talend). - Proven experience with real-time data ingestion and processing using platforms such as AWS Glue, Apache Kafka, AWS Kinesis, or similar. - Proficiency with AWS S3, AWS Glue, AWS Redshift, AWS Lake Formation, and potentially AWS EMR. - Strong background in traditional data warehousing concepts, dimensional modeling, and DWH design principles. - Proficient in SQL and at least one scripting language (e.g., Python, Scala) for data manipulation and automation. - Strong understanding of relational databases and NoSQL databases. - Experience with version control systems (e.g., Git). - Excellent analytical and problem-solving skills with attention to detail. - Strong verbal and written communication skills for conveying complex technical concepts to diverse audiences. Preferred Qualifications: - Certifications in AWS Data Analytics or related areas.,

As a Data Architect, you will be responsible for leading Data related projects in the field of Reporting and Analytics. With over 10 years of relevant work experience, you will design, build, and maintain scalable data lake and data warehouse in the cloud, particularly on Google Cloud Platform (GCP). Your expertise will be crucial in gathering business requirements, analyzing business needs, and defining the BI/DW architecture to deliver technical solutions for complex business and technical requirements. You will create solution prototypes, participate in technology selection, and perform POCs and technical presentations. In this role, you will architect, develop, and test scalable data warehouses and data pipelines architecture using Cloud Technologies on GCP. Your experience in SQL and NoSQL DBMS such as MS SQL Server, MySQL, PostgreSQL, DynamoDB, Cassandra, and MongoDB will be essential. You will design and develop scalable ETL processes, including error handling, and demonstrate proficiency in query and program languages like MS SQL Server, T-SQL, PostgreSQL, MySQL, Python, and R. Additionally, you will prepare data structures for advanced analytics and self-service reporting using tools like MS SQL, SSIS, and SSRS. Experience with cloud-based technologies such as PowerBI, Tableau, Azure Data Factory, Azure Synapse, Azure Data Lake, AWS RedShift, Glue, Athena, AWS Quicksight, and Google Cloud Platform will be beneficial. In addition, familiarity with Agile development environment, pairing DevOps with CI/CD pipelines, and having an AI/ML background are considered good to have for this role. (ref:hirist.tech),

As an Associate/Architect - Data (AbInitio) at Quantiphi, you will play a crucial role in migrating ETL jobs from existing Ab Initio to AWS Cloud. Your responsibilities will include designing and implementing a migration strategy, interpreting complex graphs and jobs in Ab Initio, and assisting the Data Engineering team in understanding business logic and data sources. You will be expected to create high-level block diagrams and flows of jobs, assist in validating output data generated through Spark code, and serve as a technical point of contact between clients and the offshore technical team. Strong communication skills to convey technical roadmaps, challenges, and mitigation strategies are essential for success in this role. The ideal candidate will have at least 7 years of experience working with Ab Initio, along with a solid understanding of SDLC concepts and processes. Additionally, familiarity with Python, Pyspark, AWS Glue, Lambda, Redshift, automation, and CICD tools would be considered advantageous. At Quantiphi, we foster a global and diverse culture that values transparency, integrity, learning, and growth. If you thrive in an environment that encourages innovation and personal growth, then a career with us would be a perfect fit for you. Join our team of happy, enthusiastic over-achievers and experience wild growth both professionally and personally.,

As a Data Architect, you will leverage your 10+ years of relevant work experience to lead Data related projects focused on Reporting and Analytics. Your responsibilities will include designing, building, and maintaining scalable data lake and data warehouse solutions in the cloud, specifically on Google Cloud Platform (GCP). You will be expected to excel in gathering business requirements, analyzing business needs, and defining the BI/DW architecture to deliver technical solutions for complex business and technical requirements. Your role will involve creating solution prototypes, participating in technology selection, conducting proof of concepts (POC), and delivering technical presentations. In this position, you will architect, develop, and test scalable data warehouses and data pipelines using Cloud Technologies on GCP. Your expertise in SQL and NoSQL database management systems such as MS SQL Server, MySQL, PostgreSQL, DynamoDB, Cassandra, and MongoDB will be essential for designing and developing scalable ETL processes, including error handling. Your proficiency in query and programming languages such as MS SQL Server, T-SQL, PostgreSQL, MySQL, Python, and R will be crucial for preparing data structures for advanced analytics and self-service reporting using tools like MS SQL, SSIS, and SSRS. Additionally, you will be responsible for scripting stored procedures, database snapshots backups, and data archiving. Experience with cloud-based technologies such as PowerBI, Tableau, Azure Data Factory, Azure Synapse, Azure Data Lake, AWS RedShift, Glue, Athena, AWS Quicksight, and Google Cloud Platform will be advantageous. In addition, familiarity with an Agile development environment, AI/ML background, and expertise in DevOps with CI/CD pipelines are considered good to have skills. Your core skills will include proficiency in data warehousing, AWS RedShift, MongoDB, GCP, analytics, data lake, Agile methodologies, PowerBI, ETL processes, business intelligence, R programming, CI/CD pipelines, SQL, DynamoDB, Azure Data Factory, NoSQL databases, Cassandra, DevOps practices, Python, Tableau, and T-SQL.,