1133 Dataflow Jobs - Page 25

Equifax is seeking creative, high-energy and driven software engineers with hands-on development skills to work on a variety of meaningful projects. Our software engineering positions provide you the opportunity to join a team of talented engineers working with leading-edge technology. You are ideal for this position if you are a forward-thinking, committed, and enthusiastic software engineer who is passionate about technology. What You’ll Do Design, develop, and operate high scale applications across the full engineering stack. Design, develop, test, deploy, maintain, and improve software. Apply modern software development practices (serverless computing, microservices architecture, CI/CD, infrastructure-as-code, etc.) Work across teams to integrate our systems with existing internal systems, Data Fabric, CSA Toolset. Participate in technology roadmap and architecture discussions to turn business requirements and vision into reality. Participate in a tight-knit, globally distributed engineering team. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on network, or service operations and quality. Research, create, and develop software applications to extend and improve on Equifax Solutions. Manage sole project priorities, deadlines, and deliverables. Collaborate on scalability issues involving access to data and information. Actively participate in Sprint planning, Sprint Retrospectives, and other team activity What Experience You Need Bachelor's degree or equivalent experience 5+ years of software engineering experience 5+ years experience writing, debugging, and troubleshooting code in mainstream Java, SpringBoot, TypeScript/JavaScript, HTML, CSS 5+ years experience with Cloud technology: GCP, AWS, or Azure 5+ years experience designing and developing cloud-native solutions 5+ years experience designing and developing microservices using Java, SpringBoot, GCP SDKs, GKE/Kubernetes 5+ years experience deploying and releasing software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs What could set you apart Self-starter that identifies/responds to priority shifts with minimal supervision. Experience designing and developing big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others UI development (e.g. HTML, JavaScript, Angular and Bootstrap) Experience with backend technologies such as JAVA/J2EE, SpringBoot, SOA and Microservices Source code control management systems (e.g. SVN/Git, Github) and build tools like Maven & Gradle. Agile environments (e.g. Scrum, XP) Relational databases (e.g. SQL Server, MySQL) Atlassian tooling (e.g. JIRA, Confluence, and Github) Developing with modern JDK (v1.7+) Automated Testing: JUnit, Selenium, LoadRunner, SoapUI Cloud Certification strongly preferred Show more Show less

Job Summary Google Cloud Platform (GCP) Services - Hands-on experience with GCP Cloud Storage, Cloud Composer, and Dataflow ETL and Data Pipeline Development - Strong knowledge of building end-to-end data pipelines, including data ingestion, transformation, and broadcasting across heterogeneous data systems. Database Technologies- Strong in Complex SQL. Proficiency in SQL and NoSQL databases (e.g., MongoDB, PostgreSQL), with the ability to write complex queries and optimize performance. Programming Skills (Python, Java, or Scala) - Proficient in at least one programming language for developing scalable data solutions and automation scripts. CI/CD and DevOps Tools - Leveraging tools like GitHub, CircleCI, and Harness to automate deployment workflows and manage data pipeline releases efficiently. Application Deployment & Observability - Experience in production deployment, issue triage, and use of observability tools and best practices. Show more Show less

Job Summary JD GCP Data Engineer Responsibilities: ¿ Design, develop, and maintain data pipelines using GCP services such as Dataflow, BigQuery, and Pub/Sub. ¿ Implement and manage data warehouse solutions using BigQuery, ensuring data is stored securely and efficiently. ¿ Use Pub/Sub for real time data ingestion and streaming analytics. ¿ Provision and manage GCP infrastructure using Terraform, ensuring best practices in IaC are followed. ¿ Optimize data storage and retrieval processes to enhance performance and reduce costs. ¿ Monitor and troubleshoot data pipeline issues, ensuring high availability and reliability of data services. ¿ Ensure data quality and integrity through robust testing and validation processes. ¿ Stay updated with the latest GCP features and best practices, integrating them into existing workflows. ¿ Document data workflows, infrastructure setups, and processes for future reference and knowledge sharing. Show more Show less

You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What you will do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What experience you need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What could set you apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes

Position: Senior Data Analytics Specialist – GCP Platform (NV50FCT RM 3314) Job Description: 5–7 years of experience in data analytics, business intelligence, or a related field. Proven expertise with Firebase Analytics and GA4, including custom event setup and user journey tracking. Advanced proficiency in BigQuery: SQL scripting, query optimization, partitioning, and clustering. Hands-on experience with Looker or Looker Studio for dashboard development and data modeling. Familiarity with other GCP services such as Cloud Storage, Cloud Functions, Pub/Sub, and Dataflow is a strong plus. Solid understanding of data privacy and governance frameworks (GDPR, CCPA, etc.). Strong analytical thinking and problem-solving abilities with attention to detail. Excellent communication skills and the ability to work effectively in cross-functional teams. Preferred Qualifications: Google Cloud certifications (e.g., Professional Data Engineer, Looker Business Analyst) Experience with A/B testing frameworks and experimentation platforms Background in product analytics or digital marketing analytics ******************************************************************************************************************************************* Job Category: Digital_Cloud_Web Technologies Job Type: Full Time Job Location: Noida Experience: 5+ years Notice period: 0-30 days

Devops Manager Location: Ahmedabad/Hyderabad Exp: 14+ years Experience Required: 14+ years total experience, with 4–5 years in managerial roles. Technical Knowledge and Skills: Mandatory: Cloud: GCP (Complete stack from IAM to GKE) CI/CD: End-to-end pipeline ownership (GitHub Actions, Jenkins, Argo CD) IaC: Terraform, Helm • Containers: Docker, Kubernetes • DevSecOps: Vault, Trivy, OWASP Nice to Have: FinOps exposure for cost optimization Big Data tools familiarity (BigQuery, Dataflow) Familiarity with Kong, Anthos, Istio Scope: Lead DevOps team across multiple pods and products Define roadmap for automation, security, and CI/CD Ensure operational stability of deployment pipelines Roles and Responsibilities: Architect and guide implementation of enterprise-grade CI/CD pipelines that support multi-environment deployments, microservices architecture, and zero downtime delivery practices. Oversee Infrastructure-as-Code initiatives to establish consistent and compliant cloud provisioning using Terraform, Helm, and policy-as-code integrations. Champion DevSecOps practices by embedding security controls throughout the pipeline—ensuring image scanning, secrets encryption, policy checks, and runtime security enforcement Lead and manage a geographically distributed DevOps team, setting performance expectations, development plans, and engagement strategies. • Drive cross-functional collaboration with engineering, QA, product, and SRE teams to establish integrated DevOps governance practices. Develop a framework for release readiness, rollback automation, change control, and environment reconciliation processes. Monitor deployment health, release velocity, lead time to recovery, and infrastructure cost optimization through actionable DevOps metrics dashboards Serve as the primary point of contact for C-level stakeholders during major infrastructure changes, incident escalations, or audits. Own the budgeting and cost management strategy for DevOps tooling, cloud consumption, and external consulting partnerships. Identify, evaluate, and onboard emerging DevOps technologies, ensuring team readiness through structured onboarding, POCs, and knowledge sessions. Foster a culture of continuous learning, innovation, and ownership—driving internal tech talks, hackathons, and community engagement Show more Show less

We are looking for an experienced and motivated Senior GCP Data Engineer to join our dynamic data team. In this role, you will be responsible for designing, building, and optimizing data pipelines, implementing advanced analytics solutions, and maintaining robust data infrastructure using Google Cloud Platform (GCP) services. You will play a key role in enabling data-driven decision-making and enhancing the performance and scalability of our data ecosystem. Key Responsibilities: Design, implement, and optimize data pipelines using Google Cloud Platform (GCP) services, including Compute Engine , BigQuery , Cloud Pub/Sub , Dataflow , Cloud Storage , and AlloyDB . Lead the design and optimization of schema for large-scale data systems, ensuring data consistency, integrity, and scalability. Work closely with cross-functional teams to understand data requirements and deliver efficient, high-performance solutions. Design and execute complex SQL queries for BigQuery and other databases, ensuring optimal performance and efficiency. Implement efficient data processing workflows and streaming data solutions using Cloud Pub/Sub and Dataflow . Develop and maintain data models, schemas, and data marts to ensure consistency and scalability across datasets. Ensure the scalability, reliability, and security of cloud-based data architectures. Optimize cloud storage, compute, and query performance, driving cost-effective solutions. Collaborate with data scientists, analysts, and software engineers to create actionable insights and drive business outcomes. Implement best practices for data management, including governance, quality, and monitoring of data pipelines. Provide mentorship and guidance to junior data engineers and collaborate with them to achieve team goals. Required Qualifications: Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent work experience). 5+ years of experience in data engineering, with a strong focus on Google Cloud Platform (GCP) . Extensive hands-on experience with GCP Compute Engine , BigQuery , Cloud Pub/Sub , Dataflow , Cloud Storage , and AlloyDB . Strong expertise in SQL for query optimization and performance tuning in large-scale datasets. Solid experience in designing data schemas, data pipelines, and ETL processes. Strong understanding of data modeling techniques, and experience with schema design for both transactional and analytical systems. Proven experience optimizing BigQuery performance, including partitioning, clustering, and cost optimization strategies. Experience with managing and processing streaming data and batch data processing workflows. Knowledge of AlloyDB for managing transactional databases in the cloud and integrating them into data pipelines. Familiarity with data security, governance, and compliance best practices on GCP. Excellent problem-solving skills, with the ability to troubleshoot complex data issues and find efficient solutions. Strong communication and collaboration skills, with the ability to work with both technical and non-technical stakeholders. Preferred Qualifications: Bachelor's/Masters degree in Computer Science, Data Engineering, or a related field. Familiarity with infrastructure as code tools like Terraform or Cloud Deployment Manager . GCP certifications (e.g., Google Cloud Professional Data Engineer or Cloud Architect ).

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: Execute the business analytics agenda in conjunction with analytics team leaders Work with best-in-class external partners who leverage analytics tools and processes Use models/algorithms to uncover signals/patterns and trends to drive long-term business performance Execute the business analytics 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 analytic leaders Understanding in best-in-class analytics practices Knowledge of Indicators (KPI's) and scorecards Knowledge of BI tools like Tableau, Excel, Alteryx, R, Python, etc. is a plus Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It with Pride In This Role As a DaaS Data Engineer, you will have the opportunity to design and build scalable, secure, and cost-effective cloud-based data solutions. You will develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes, ensuring data quality and validation processes to maintain data accuracy and integrity. You will ensure efficient data storage and retrieval for optimal performance, and collaborate closely with data teams, product owners, and other stakeholders to stay updated with the latest cloud technologies and best practices. Role & Responsibilities: Design and Build: Develop and implement scalable, secure, and cost-effective cloud-based data solutions. Manage Data Pipelines: Develop and maintain data pipelines to extract, transform, and load data into data warehouses or data lakes. Ensure Data Quality: Implement data quality and validation processes to ensure data accuracy and integrity. Optimize Data Storage: Ensure efficient data storage and retrieval for optimal performance. Collaborate and Innovate: Work closely with data teams, product owners, and stay updated with the latest cloud technologies and best practices to remain current in the field. Technical Requirements: Programming: Python, PySpark, Go/Java Database: SQL, PL/SQL ETL & Integration: DBT, Databricks + DLT, AecorSoft, Talend, Informatica/Pentaho/Ab-Initio, Fivetran. Data Warehousing: SCD, Schema Types, Data Mart. Visualization: Databricks Notebook, PowerBI, Tableau, Looker. GCP Cloud Services: Big Query, GCS, Cloud Function, PubSub, Dataflow, DataProc, Dataplex. AWS Cloud Services: S3, Redshift, Lambda, Glue, CloudWatch, EMR, SNS, Kinesis. Supporting Technologies: Graph Database/Neo4j, Erwin, Collibra, Ataccama DQ, Kafka, Airflow. Experience with RGM.ai product would have an added advantage. Soft Skills: Problem-Solving: The ability to identify and solve complex data-related challenges. Communication: Effective communication skills to collaborate with Product Owners, analysts, and stakeholders. Analytical Thinking: The capacity to analyse data and draw meaningful insights. Attention to Detail: Meticulousness in data preparation and pipeline development. Adaptability: The ability to stay updated with emerging technologies and trends in the data engineering field. 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

TCS Hiring !!! Role: Google Data Engineer Experience: 3-5 years Location: Hyderabad & Chennai Job Description: Experience level of 3 to 5 years of relevant experience in data engineering, data warehousing, or a related field. Experience with dashboarding tools like plx dashboard and looker studio Experience with building data pipelines, reports, best practices and frameworks. Experience with design and development of scalable and actionable solutions (dashboards, automated collateral, web applications). Experience with code refactoring for optimal performance. Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources. Familiarity with non-relational data storage systems (NoSQL and distributed database management systems). Strong proficiency in SQL, NoSQL, ETL tools, Big Query and at least one programming language (e.g., Python, Java). Strong understanding of data structures, algorithms, and software design principles. Experience with data modeling techniques and methodologies. Proficiency in troubleshooting and debugging complex data-related issues. Ability to work independently and as part of a team. Experience Cloud Storage or equivalent cloud platforms Knowledge of Big Query ingress and egress patterns Experience in writing Airflow DAGs Knowledge of pub sub, dataflow or any declarative data pipeline tools using batch and streaming ingestion Other GCP Services: Vertex AI Show more Show less

Role : Database Engineer Location : Remote Notice Period : 30 Days 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. Show more Show less

Data Engineer - Google Cloud Location : Remote, India About Us Aviato Consulting is looking for a highly skilled and motivated Data Engineer to join our expanding team. This role is ideal for someone with a deep understanding of cloud-based data solutions, with a focus on Google Cloud (GCP) and associated technologies. GCP certification is mandatory for this position to ensure the highest level of expertise and professionalism. You will work directly with clients, translating their business requirements into scalable data solutions, while providing technical expertise and guidance. Key Responsibilities Client Engagement : Work closely with clients to understand business needs, gather technical requirements, and design solutions leveraging GCP services. Data Pipeline Design & Development : Build and manage scalable data pipelines using tools such as Apache Beam, Cloud Dataflow, and Cloud Composer. Data Warehousing & Lake Solutions : Architect, implement, and optimize BigQuery-based data lakes and warehouses. Real-Time Data Processing : Implement and manage streaming data pipelines using Kafka, Pub/Sub, and similar technologies. Data Analysis & Visualization : Create insightful data dashboards and visualizations using tools like Looker, Data Studio, or Tableau. Technical Leadership & Mentorship : Provide guidance and mentorship to team members and clients, helping them leverage the full potential of Google Cloud. Required Qualifications Experience : 5+ years as a Data Engineer working with cloud-based platforms. Proven experience in Python with libraries like Pandas and NumPy. Strong understanding and experience with FastAPI for building APIs. Expertise in building data pipelines using Apache Beam, Cloud Dataflow, or similar tools. Solid knowledge of Kafka for real-time data streaming. Proficiency with BigQuery, Google Pub/Sub, and other Google Cloud services. Familiarity with Apache Hadoop for distributed data processing. Technical Skills Strong understanding of data architecture and processing techniques. Experience with big data environments and tools like Apache Hadoop. Solid understanding of ETL pipelines, data ingestion, transformation, and storage. Knowledge of data modeling, data warehousing, and big data management principles. Certifications Google Cloud certification (Professional Data Engineer, Cloud Architect) is mandatory for this role. Soft Skills Excellent English communication skills. Client-facing experience and the ability to manage client relationships effectively. Strong problem-solving skills with a results-oriented approach. Preferred Qualifications Visualization Tools : Experience with tools like Looker, Power BI, or Tableau. Benefits Competitive salary and benefits package. Opportunities to work with cutting-edge cloud technologies with large customers. Collaborative work environment that encourages learning and professional growth. A chance to work on high-impact projects for leading clients in diverse industries. If you're passionate about data engineering, cloud technologies, and solving complex data problems for clients, wed love to hear from you! (ref:hirist.tech) Show more Show less

Job Description Support the day-to-day operations of these GCP-based data pipelines, ensuring data governance, reliability, and performance optimization. Hands-on experience with GCP data services such as Dataflow, BigQuery, Dataproc, Pub/Sub, and real-time streaming architectures is preferred.The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. This role requires a flexible working schedule, including potential weekend support for critical operations, while maintaining a 40-hour work week.The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives. A key aspect of the MDLZ Google cloud BigQuery platform is handling the complexity of inbound data, which often does not follow a global design (e.g., variations in channel inventory, customer PoS, hierarchies, distribution, and promo plans). You will assist in ensuring the robust operation of pipelines that translate this varied inbound data into the standardized o9 global design. This also includes man '8+ years of overall industry experience and minimum of 8-10 years of experience building and deploying large scale data processing pipelines in a production environment Focus on excellence: Has practical experience of Data-Driven Approaches, Is familiar with the application of Data Security strategy, Is familiar with well know data engineering tools and platforms Technical depth and breadth : Able to build and operate Data Pipelines, Build and operate Data Storage, Has worked on big data architecture within Distributed Systems. Is familiar with Infrastructure definition and automation in this context. Is aware of adjacent technologies to the ones they have worked on. Can speak to the alternative tech choices to that made on their projects. Implementation and automation of Internal data extraction from SAP BW / HANA Implementation and automation of External data extraction from openly available internet data sources via APIs Data cleaning, curation and enrichment by using Alteryx, SQL, Python, R, PySpark, SparkR Preparing consolidated DataMart for use by Data Scientists and managing SQL Databases Exposing data via Alteryx, SQL Database for consumption in Tableau Data documentation maintenance/update Collaboration and workflow using a version control system (e.g., Git Hub) Learning ability : Is self-reflective, Has a hunger to improve, Has a keen interest to drive their own learning. Applies theoretical knowledge to practice Flexible Working Hours: This role requires the flexibility to work non-traditional hours, including providing support during off-hours or weekends for critical data pipeline job runs, deployments, or incident response, while ensuring the total work commitment remains a 40-hour week. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.Data engineering Concepts: Experience in working with data lake, data warehouse, data mart and Implemented ETL/ELT and SCD concepts. ETL or Data integration tool: Experience in Talend is highly desirable. Analytics: Fluent with SQL, PL/SQL and have used analytics tools like Big Query for data analytics Cloud experience: Experienced in GCP services like cloud function, cloud run, data flow, data proc and big query. Data sources: Experience of working with structure data sources like SAP, BW, Flat Files, RDBMS etc. and semi structured data sources like PDF, JSON, XML etc. Programming: Understanding of OOPs concepts and hands-on experience with Python/Java for programming and scripting. Data Processing: Experience in working with any of the Data Processing Platforms like Dataflow, Databricks. Orchestration: Experience in orchestrating/scheduling data pipelines using any of the tools like Airflow and Alteryx Keep our data separated and secure across national boundaries through multiple data centers and Azure regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Skills And Experience Rich experience in working with FMCG industry. Deep knowledge in manipulating, processing, and extracting value from datasets; + 5 years of experience in data engineering, business intelligence, data science, or related field; Proficiency with Programming Languages: SQL, Python, R Spark, PySpark, SparkR, SQL for data processing; Strong project management skills and ability to plan and prioritize work in a fast-paced environment; Experience with: MS Azure Data Factory, MS Azure Data Lake Store, SQL Database, SAP BW/ ECC / HANA, Alteryx, Tableau; Ability to think creatively, highly-driven and self-motivated; Knowledge of SAP BW for HANA (Extractors, Transformations, Modeling aDSOs, Queries, OpenHubs) No Relocation support available Business Unit Summary Headquartered in Singapore, Mondelēz International’s Asia, Middle East and Africa (AMEA) region is comprised of six business units, has more than 21,000 employees and operates in more than 27 countries including Australia, China, Indonesia, Ghana, India, Japan, Malaysia, New Zealand, Nigeria, Philippines, Saudi Arabia, South Africa, Thailand, United Arab Emirates and Vietnam. Seventy-six nationalities work across a network of more than 35 manufacturing plants, three global research and development technical centers and in offices stretching from Auckland, New Zealand to Casablanca, Morocco. Mondelēz International in the AMEA region is the proud maker of global and local iconic brands such as Oreo and belVita biscuits, Kinh Do mooncakes, Cadbury, Cadbury Dairy Milk and Milka chocolate, Halls candy, Stride gum, Tang powdered beverage and Philadelphia cheese. We are also proud to be named a Top Employer in many of our markets. 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

Job Description Support the day-to-day operations of these GCP-based data pipelines, ensuring data governance, reliability, and performance optimization. Hands-on experience with GCP data services such as Dataflow, BigQuery, Dataproc, Pub/Sub, and real-time streaming architectures is preferred.The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.This role requires a flexible working schedule, including potential weekend support for critical operations, while maintaining a 40-hour work week. A key aspect of the MDLZ DataHub Google BigQuery platform is handling the complexity of inbound data, which often does not follow a global design (e.g., variations in channel inventory, customer PoS, hierarchies, distribution, and promo plans). You will assist in ensuring the robust operation of pipelines that translate this varied inbound data into the standardized o9 global design. This also includes managing pipelines for different data drivers (> 6 months vs. 0-6 months), ensuring consistent input to o9. '6+ years of overall industry experience and minimum of 6-8 years of experience building and deploying large scale data processing pipelines in a production environment Focus on excellence: Has practical experience of Data-Driven Approaches, Is familiar with the application of Data Security strategy, Is familiar with well know data engineering tools and platforms Technical depth and breadth : Able to build and operate Data Pipelines, Build and operate Data Storage, Has worked on big data architecture within Distributed Systems. Is familiar with Infrastructure definition and automation in this context. Is aware of adjacent technologies to the ones they have worked on. Can speak to the alternative tech choices to that made on their projects. Implementation and automation of Internal data extraction from SAP BW / HANA Implementation and automation of External data extraction from openly available internet data sources via APIs Data cleaning, curation and enrichment by using Alteryx, SQL, Python, R, PySpark, SparkR Preparing consolidated DataMart for use by Data Scientists and managing SQL Databases Exposing data via Alteryx, SQL Database for consumption in Tableau Data documentation maintenance/update Collaboration and workflow using a version control system (e.g., Git Hub) Learning ability : Is self-reflective, Has a hunger to improve, Has a keen interest to drive their own learning. Applies theoretical knowledge to practice Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.Data engineering Concepts: Experience in working with data lake, data warehouse, data mart and Implemented ETL/ELT and SCD concepts. ETL or Data integration tool: Experience in Talend is highly desirable. Analytics: Fluent with SQL, PL/SQL and have used analytics tools like Big Query for data analytics Cloud experience: Experienced in GCP services like cloud function, cloud run, data flow, data proc and big query. Data sources: Experience of working with structure data sources like SAP, BW, Flat Files, RDBMS etc. and semi structured data sources like PDF, JSON, XML etc. Flexible Working Hours: This role requires the flexibility to work non-traditional hours, including providing support during off-hours or weekends for critical data pipeline job runs, deployments, or incident response, while ensuring the total work commitment remains a 40-hour week. Data Processing: Experience in working with any of the Data Processing Platforms like Dataflow, Databricks. Orchestration: Experience in orchestrating/scheduling data pipelines using any of the tools like Airflow and Alteryx Keep our data separated and secure across national boundaries through multiple data centers and Azure regions. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Skills And Experience Deep knowledge in manipulating, processing, and extracting value from datasets; Atleast 2 years of FMCG/CPG industry experience. + 5 years of experience in data engineering, business intelligence, data science, or related field; Proficiency with Programming Languages: SQL, Python, R Spark, PySpark, SparkR, SQL for data processing; Strong project management skills and ability to plan and prioritize work in a fast-paced environment; Experience with: MS Azure Data Factory, MS Azure Data Lake Store, SQL Database, SAP BW/ ECC / HANA, Alteryx, Tableau; Ability to think creatively, highly-driven and self-motivated; Knowledge of SAP BW for HANA (Extractors, Transformations, Modeling aDSOs, Queries, OpenHubs) No Relocation support available Business Unit Summary Headquartered in Singapore, Mondelēz International’s Asia, Middle East and Africa (AMEA) region is comprised of six business units, has more than 21,000 employees and operates in more than 27 countries including Australia, China, Indonesia, Ghana, India, Japan, Malaysia, New Zealand, Nigeria, Philippines, Saudi Arabia, South Africa, Thailand, United Arab Emirates and Vietnam. Seventy-six nationalities work across a network of more than 35 manufacturing plants, three global research and development technical centers and in offices stretching from Auckland, New Zealand to Casablanca, Morocco. Mondelēz International in the AMEA region is the proud maker of global and local iconic brands such as Oreo and belVita biscuits, Kinh Do mooncakes, Cadbury, Cadbury Dairy Milk and Milka chocolate, Halls candy, Stride gum, Tang powdered beverage and Philadelphia cheese. We are also proud to be named a Top Employer in many of our markets. 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

Job Description Looking for a savvy Data Engineer to join team of Modeling / Architect experts. The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for cross functional teams. The ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up. The Data Engineer will support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation of products and data initiatives.This role requires a flexible working schedule, including potential weekend support for critical operations, while maintaining a 40-hour work week. In this role, you will assist in maintaining the MDLZ DataHub Google BigQuery data pipelines and corresponding platforms (on-prem and cloud), working closely with global teams on DataOps initiatives. The D4GV platform spans across three key GCP instances: NALA, MEU, and AMEA, supporting the global rollout of o9 across all Mondelēz BUs over the next three years 5+ years of overall industry experience and minimum of 2-4 years of experience building and deploying large scale data processing pipelines in a production environment Focus on excellence: Has practical experience of Data-Driven Approaches, Is familiar with the application of Data Security strategy, Is familiar with well know data engineering tools and platforms Technical depth and breadth : Able to build and operate Data Pipelines, Build and operate Data Storage, Has worked on big data architecture within Distributed Systems. Is familiar with Infrastructure definition and automation in this context. Is aware of adjacent technologies to the ones they have worked on. Can speak to the alternative tech choices to that made on their projects. Implementation and automation of Internal data extraction from SAP BW / HANA Implementation and automation of External data extraction from openly available internet data sources via APIs Data cleaning, curation and enrichment by using Alteryx, SQL, Python, R, PySpark, SparkR Data ingestion and management in Hadoop / Hive Preparing consolidated DataMart for use by Data Scientists and managing SQL Databases Exposing data via Alteryx, SQL Database for consumption in Tableau Data documentation maintenance/update Collaboration and workflow using a version control system (e.g., Git Hub) Learning ability : Is self-reflective, Has a hunger to improve, Has a keen interest to drive their own learning. Applies theoretical knowledge to practice Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics. Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs. Flexible Working Hours: This role requires the flexibility to work non-traditional hours, including providing support during off-hours or weekends for critical data pipeline job runs, deployments, or incident response, while ensuring the total work commitment remains a 40-hour week. Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. Work with data and analytics experts to strive for greater functionality in our data systems. Skills And Experience Deep knowledge in manipulating, processing, and extracting value from datasets; support the day-to-day operations of these GCP-based data pipelines, ensuring data governance, reliability, and performance optimization. Hands-on experience with GCP data services such as Dataflow, BigQuery, Dataproc, Pub/Sub, and real-time streaming architectures is preferred. + 5 years of experience in data engineering, business intelligence, data science, or related field; Proficiency with Programming Languages: SQL, Python, R Spark, PySpark, SparkR, SQL for data processing; Strong project management skills and ability to plan and prioritize work in a fast-paced environment; Experience with: MS Azure Data Factory, MS Azure Data Lake Store, SQL Database, SAP BW/ ECC / HANA, Alteryx, Tableau; Ability to think creatively, highly-driven and self-motivated; Knowledge of SAP BW for HANA (Extractors, Transformations, Modeling aDSOs, Queries, OpenHubs) No Relocation support available Business Unit Summary Headquartered in Singapore, Mondelēz International’s Asia, Middle East and Africa (AMEA) region is comprised of six business units, has more than 21,000 employees and operates in more than 27 countries including Australia, China, Indonesia, Ghana, India, Japan, Malaysia, New Zealand, Nigeria, Philippines, Saudi Arabia, South Africa, Thailand, United Arab Emirates and Vietnam. Seventy-six nationalities work across a network of more than 35 manufacturing plants, three global research and development technical centers and in offices stretching from Auckland, New Zealand to Casablanca, Morocco. Mondelēz International in the AMEA region is the proud maker of global and local iconic brands such as Oreo and belVita biscuits, Kinh Do mooncakes, Cadbury, Cadbury Dairy Milk and Milka chocolate, Halls candy, Stride gum, Tang powdered beverage and Philadelphia cheese. We are also proud to be named a Top Employer in many of our markets. 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

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What You Will Do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What Experience You Need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What Could Set You Apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes We offer a hybrid work setting, comprehensive compensation and healthcare packages, attractive paid time off, and organizational growth potential through our online learning platform with guided career tracks. Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference! Who is Equifax? At Equifax, we believe knowledge drives progress. As a global data, analytics and technology company, we play an essential role in the global economy by helping employers, employees, financial institutions and government agencies make critical decisions with greater confidence. We work to help create seamless and positive experiences during life’s pivotal moments: applying for jobs or a mortgage, financing an education or buying a car. Our impact is real and to accomplish our goals we focus on nurturing our people for career advancement and their learning and development, supporting our next generation of leaders, maintaining an inclusive and diverse work environment, and regularly engaging and recognizing our employees. Regardless of location or role, the individual and collective work of our employees makes a difference and we are looking for talented team players to join us as we help people live their financial best. Equifax is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Show more Show less

Equifax is where you can power your possible. If you want to achieve your true potential, chart new paths, develop new skills, collaborate with bright minds, and make a meaningful impact, we want to hear from you. You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What You Will Do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What Experience You Need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What Could Set You Apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes We offer a hybrid work setting, comprehensive compensation and healthcare packages, attractive paid time off, and organizational growth potential through our online learning platform with guided career tracks. Are you ready to power your possible? Apply today, and get started on a path toward an exciting new career at Equifax, where you can make a difference! Who is Equifax? At Equifax, we believe knowledge drives progress. As a global data, analytics and technology company, we play an essential role in the global economy by helping employers, employees, financial institutions and government agencies make critical decisions with greater confidence. We work to help create seamless and positive experiences during life’s pivotal moments: applying for jobs or a mortgage, financing an education or buying a car. Our impact is real and to accomplish our goals we focus on nurturing our people for career advancement and their learning and development, supporting our next generation of leaders, maintaining an inclusive and diverse work environment, and regularly engaging and recognizing our employees. Regardless of location or role, the individual and collective work of our employees makes a difference and we are looking for talented team players to join us as we help people live their financial best. Equifax is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. Show more Show less

Join us in bringing joy to customer experience. Five9 is a leading provider of cloud contact center software, bringing the power of cloud innovation to customers worldwide. Living our values everyday results in our team-first culture and enables us to innovate, grow, and thrive while enjoying the journey together. We celebrate diversity and foster an inclusive environment, empowering our employees to be their authentic selves. The Data Engineer will help design and implement a Google Cloud Platform (GCP) Data Lake, build scalable data pipelines, and ensure seamless access to data for business intelligence and data science tools. They will support a wide range of projects while collaborating closely with management teams and business leaders. The ideal candidate will have a strong understanding of data engineering principles, data warehousing concepts, and the ability to document technical knowledge into clear processes and procedures. This position is based out of one of the offices of our affiliate Acqueon Technologies in India, and will adopt the hybrid work arrangements of that location. You will be a member of the Acqueon team with responsibilities supporting Five9 products, collaborating with global teammates based primarily in the United States. Responsibilities Design, implement, and maintain a scalable Data Lake on GCP to centralize structured and unstructured data from various sources (databases, APIs, cloud storage). Utilize GCP services including BigQuery, Dataflow, Pub/Sub, and Cloud Storage to optimize and manage data workflows, ensuring scalability, performance, and security. Collaborate closely with data analytics and data science teams to understand data needs, ensuring data is properly prepared for consumption by various systems (e.g. DOMO, Looker, Databricks) Implement best practices for data quality, consistency, and governance across all data pipelines and systems, ensuring compliance with internal and external standards. Continuously monitor, test, and optimize data workflows to improve performance, cost efficiency, and reliability. Maintain comprehensive technical documentation of data pipelines, systems, and architecture for knowledge sharing and future development. Requirements Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related quantitative field (e.g. Mathematics, Statistics, Engineering). 3+ years of experience using GCP Data Lake and Storage Services. Certifications in GCP are preferred (e.g. Professional Cloud Developer, Professional Cloud Database Engineer). Advanced proficiency with SQL, with experience in writing complex queries, optimizing for performance, and using SQL in large-scale data processing workflows. Proficiency in programming languages such as Python, Java, or Scala, with practical experience building data pipelines, automating data workflows, and integrating APIs for data ingestion. Five9 embraces diversity and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. The more inclusive we are, the better we are. Five9 is an equal opportunity employer. View our privacy policy, including our privacy notice to California residents here: https://www.five9.com/pt-pt/legal. Note: Five9 will never request that an applicant send money as a prerequisite for commencing employment with Five9. Show more Show less

Tata Consultancy Services is hiring Google Data Engineer !!! Role**Google Data Engineer EXP***3-5 years Location***Bangalore, Chennai, Hyderabad Experience Experience level of 3 to 5 years in data engineering, data warehousing, or a related field. Experience with dashboarding tools like plx dashboard and looker studio Experience with building data pipelines, reports, best practices and frameworks. Experience with design and development of scalable and actionable solutions (dashboards, automated collateral, web applications). Experience with code refactoring for optimal performance. Experience writing and maintaining ETLs which operate on a variety of structured and unstructured sources. Familiarity with non-relational data storage systems (NoSQL and distributed database management systems). Skills Strong proficiency in SQL, NoSQL, ETL tools, BigQuery and at least one programming language (e.g., Python, Java). Strong understanding of data structures, algorithms, and software design principles. Experience with data modeling techniques and methodologies. Proficiency in troubleshooting and debugging complex data-related issues. Ability to work independently and as part of a team. Responsibilities Data Pipeline Development: Design, implement, and maintain robust and scalable data pipelines to extract, transform, and load data from various sources into our data warehouse or data lake. Data Modeling and Warehousing: Collaborate with data scientists and analysts to design and implement data models that optimize query performance and support complex analytical workloads. Cloud Infrastructure: Leverage Google Cloud and other internal storage platforms to build and manage scalable and cost-effective data storage and processing solutions. Data Quality Assurance: Implement data quality checks and monitoring processes to ensure the accuracy, completeness, and consistency of data. Performance Optimization: Continuously monitor and optimize data pipelines and queries for performance and efficiency. Collaboration: Work closely with data scientists, analysts, and other stakeholders to understand their data needs and deliver solutions that meet their requirements. Desirable Experience Cloud Storage or equivalent cloud platforms Knowledge of BigQuery ingress and egress patterns Experience in writing Airflow DAGs Knowledge of pubsub,dataflow or any declarative data pipeline tools using batch and streaming ingestion Other GCP Services: Vertex AI Interested candidates can apply !!! Show more Show less

Introduction We are looking for candidates with 10 +years of experience in data architect role. 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. Implement best practices for data security, privacy, and compliance in cloud environments. Integrate machine learning workflows with data pipelines and analytics tools. Define data governance frameworks and manage data lineage. Lead data modeling efforts to ensure consistency, accuracy, and performance across systems. Optimize cloud infrastructure for scalability, performance, and reliability. Mentor junior team members and ensure adherence to architectural standards. Collaborate with DevOps teams to implement Infrastructure as Code (Terraform, Cloud Deployment Manager). Ensure high availability and disaster recovery solutions are built into data systems. Conduct technical reviews, audits, and performance tuning for data solutions. Design solutions for multi-region and multi-cloud data architecture. Stay updated on emerging technologies and trends in data engineering and GCP. Drive innovation in data architecture, recommending new tools and services on GCP. Certifications : Google Cloud Certification is Preferred. Primary Skills : 7+ years of experience in data architecture, with at least 3 years in GCP environments. 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.

Overview: We are looking for a skilled GCP Data Engineer with 3 to 10 years of real hands-on experience in data ingestion, data engineering, data quality, data governance, and cloud data warehouse implementations using GCP data services. The ideal candidate will be responsible for designing and developing data pipelines, participating in architectural discussions, and implementing data solutions in a cloud environment. Key Responsibilities:  Collaborate with stakeholders to gather requirements and create high-level and detailed technical designs.  Develop and maintain data ingestion frameworks and pipelines from various data sources using GCP services.  Participate in architectural discussions, conduct system analysis, and suggest optimal solutions that are scalable, future-proof, and aligned with business requirements.  Design data models suitable for both transactional and big data environments, supporting Machine Learning workflows.  Build and optimize ETL/ELT infrastructure using a variety of data sources and GCP services.  Develop and implement data and semantic interoperability specifications.  Work closely with business teams to define and scope requirements.  Analyze existing systems to identify appropriate data sources and drive continuous improvement.  Implement and continuously enhance automation processes for data ingestion and data transformation.  Support DevOps automation efforts to ensure smooth integration and deployment of data pipelines.  Provide design expertise in Master Data Management (MDM), Data Quality, and Metadata Management. Skills and Qualifications:  Overall 3-10 years of hands-on experience as a Data Engineer, with at least 2-3 years of direct GCP Data Engineering experience.  Strong SQL and Python development skills are mandatory.  Solid experience in data engineering, working with distributed architectures, ETL/ELT, and big data technologies.  Demonstrated knowledge and experience with Google Cloud BigQuery is a must.  Experience with DataProc and Dataflow is highly preferred.  Strong understanding of serverless data warehousing on GCP and familiarity with DWBI modeling frameworks.  Extensive experience in SQL across various database platforms.  Any BI tools Experience is also preferred.  Experience in data mapping and data modeling.  Familiarity with data analytics tools and best practices.  Hands-on experience with one or more programming/scripting languages such as Python, JavaScript, Java, R, or UNIX Shell.  Practical experience with Google Cloud services including but not limited to: o BigQuery, BigTable o Cloud Dataflow, Cloud Dataproc o Cloud Storage, Pub/Sub o Cloud Functions, Cloud Composer o Cloud Spanner, Cloud SQL  Knowledge of modern data mining, cloud computing, and data management tools (such as Hadoop, HDFS, and Spark).  Familiarity with GCP tools like Looker, Airflow DAGs, Data Studio, App Maker, etc.  Hands-on experience implementing enterprise-wide cloud data lake and data warehouse solutions on GCP.  GCP Data Engineer Certification is highly preferred. Job Type: Full-time Pay: ₹500,298.14 - ₹1,850,039.92 per year Benefits: Health insurance Schedule: Rotational shift Work Location: In person

Position: GCP Data Engineer Company Info: Prama (HQ : Chandler, AZ, USA) Prama specializes in AI-powered and Generative AI solutions for Data, Cloud, and APIs. We collaborate with businesses worldwide to develop platforms and AI-powered products that offer valuable insights and drive business growth. Our comprehensive services include architectural assessment, strategy development, and execution to create secure, reliable, and scalable systems. We are experts in creating innovative platforms for various industries. We help clients to overcome complex business challenges. Our team is dedicated to delivering cutting-edge solutions that elevate the digital experience for corporations. Prama is headquartered in Phoenix with offices in USA, Canada, Mexico, Brazil and India. Location: Bengaluru | Gurugram | Hybrid Benefits: 5 Day Working | Career Growth | Flexible working | Potential On-site Opportunity Kindly send your CV or Resume to careers@prama.ai Primary skills: GCP, PySpark, Python, SQL, ETL Job Description: We are seeking a highly skilled and motivated GCP Data Engineer to join our team. As a GCP Data Engineer, you will play a crucial role in designing, developing, and maintaining robust data pipelines and data warehousing solutions on the Google Cloud Platform (GCP). You will work closely with data analysts, data scientists, and other stakeholders to ensure the efficient collection, transformation, and analysis of large datasets. Responsibilities: · Design, develop, and maintain scalable data pipelines using GCP tools such as Dataflow, Dataproc, and Cloud Functions. · Implement ETL processes to extract, transform, and load data from various sources into BigQuery. · Optimize data pipelines for performance, cost-efficiency, and reliability. · Collaborate with data analysts and data scientists to understand their data needs and translate them into technical solutions. · Design and implement data warehouses and data marts using BigQuery. · Model and structure data for optimal performance and query efficiency. · Develop and maintain data quality checks and monitoring processes. · Use SQL and Python (PySpark) to analyze large datasets and generate insights. · Create visualizations using tools like Data Studio or Looker to communicate data findings effectively. · Manage and maintain GCP resources, including virtual machines, storage, and networking. · Implement best practices for security, cost optimization, and scalability. · Automate infrastructure provisioning and management using tools like Terraform. Qualifications: · Strong proficiency in SQL, Python, and PySpark. · Hands-on experience with GCP services, including BigQuery, Dataflow, Dataproc, Cloud Storage, and Cloud Functions. · Experience with data warehousing concepts and methodologies. · Understanding of data modeling techniques and best practices. · Strong analytical and problem-solving skills. · Excellent communication and collaboration skills. · Experience with data quality assurance and monitoring. · Knowledge of cloud security best practices. · A passion for data and a desire to learn new technologies. Preferred Qualifications: · Google Cloud Platform certification. · Experience with machine learning and AI. · Knowledge of data streaming technologies (Kafka, Pub/Sub). · Experience with data visualization tools (Looker, Tableau, Data Studio Job Type: Full-time Pay: ₹1,200,000.00 - ₹2,000,000.00 per year Benefits: Flexible schedule Health insurance Leave encashment Paid sick time Provident Fund Work from home Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): CTC Expected CTC Notice Period (days) Experience in GCP Total Experience Work Location: Hybrid remote in Gurugram, Haryana

You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What You Will Do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What Experience You Need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What Could Set You Apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes Show more Show less

Future-Able is looking for a Data Engineer, a full-time contract role, to work for: Naked & Thriving - An organic, botanical skincare brand committed to creating high-performing, naturally derived products that are as kind to the planet as they are to your skin. Our mission is to empower individuals to embrace sustainable self-care while nurturing their natural beauty. Every product we craft reflects our dedication to sustainability, quality, and transparency, ensuring our customers feel confident with every choice they make. As we rapidly grow and expand into new categories, channels, and countries, customer satisfaction remains our top priority. Job Summary: We are seeking a Data Engineer with expertise in Python, exposure to AI & Machine Learning, and a strong understanding of eCommerce analytics to design, develop, and optimize data pipelines. The ideal candidate will work on Google Cloud infrastructure, enabling advanced insights using Google Analytics (GA4). What You Will Do: ● Develop & maintain scalable data pipelines to support analytics and AI-driven models. ● Work with Python (or equivalent programming language) for data processing and transformation. ● Implement AI & Machine Learning techniques for predictive analytics and automation. ● Optimize eCommerce data insights using GA4 and Google Analytics to drive business decisions. ● Build cloud-based data infrastructure leveraging Google Cloud services like BigQuery, Pub/Sub, and Dataflow. ● Ensure data integrity and governance across structured and unstructured datasets. ● Collaborate with cross-functional teams including product managers, analysts, and marketing professionals. ● Monitor & troubleshoot data pipelines to ensure smooth operation and performance. We are looking for: ● Proficiency in Python or a similar language (e.g., Scala). ● Experience with eCommerce analytics and tracking frameworks. ● Expertise in Google Analytics & GA4 for data-driven insights. ● Knowledge of Google Cloud Platform (GCP), including BigQuery, Cloud Functions, and Dataflow. ● Experience in designing, building, and optimizing data pipelines using ETL frameworks. ● Familiarity with data warehousing concepts and SQL-based query optimization. ● Strong problem-solving and communication skills in a fast-paced environment. What will make you stand out: ● Experience with event-driven architecture for real-time data processing. ● Understanding of marketing analytics and attribution modeling. ● Previous work in a high-growth eCommerce environment. ● Exposure of AI & Machine Learning concepts and model deployment. Benefits: ● USD Salary. ● Fully Remote Work. ● USD 50 for health insurance payment. ● 30 days of pay time off per year. ● The possibility of being selected for annual bonuses based on business performance and personal achievements. Show more Show less

You are passionate about quality and how customers experience the products you test. You have the ability to create, maintain and execute test plans in order to verify requirements. As a Quality Engineer at Equifax, you will be a catalyst in both the development and the testing of high priority initiatives. You will develop and test new products to support technology operations while maintaining exemplary standards. As a collaborative member of the team, you will deliver QA services (code quality, testing services, performance engineering, development collaboration and continuous integration). You will conduct quality control tests in order to ensure full compliance with specified standards and end user requirements. You will execute tests using established plans and scripts; documents problems in an issues log and retest to ensure problems are resolved. You will create test files to thoroughly test program logic and verify system flow. You will identify, recommend and implement changes to enhance effectiveness of QA strategies. What You Will Do Independently develop scalable and reliable automated tests and frameworks for testing software solutions. Specify and automate test scenarios and test data for a highly complex business by analyzing integration points, data flows, personas, authorization schemes and environments Develop regression suites, develop automation scenarios, and move automation to an agile continuous testing model. Pro-actively and collaboratively taking part in all testing related activities while establishing partnerships with key stakeholders in Product, Development/Engineering, and Technology Operations. What Experience You Need Bachelor's degree in a STEM major or equivalent experience 5-7 years of software testing experience Able to create and review test automation according to specifications Ability to write, debug, and troubleshoot code in Java, Springboot, TypeScript/JavaScript, HTML, CSS Creation and use of big data processing solutions using Dataflow/Apache Beam, Bigtable, BigQuery, PubSub, GCS, Composer/Airflow, and others with respect to software validation Created test strategies and plans Led complex testing efforts or projects Participated in Sprint Planning as the Test Lead Collaborated with Product Owners, SREs, Technical Architects to define testing strategies and plans. Design and development of micro services using Java, Springboot, GCP SDKs, GKE/Kubeneties Deploy and release software using Jenkins CI/CD pipelines, understand infrastructure-as-code concepts, Helm Charts, and Terraform constructs Cloud Certification Strongly Preferred What Could Set You Apart An ability to demonstrate successful performance of our Success Profile skills, including: Attention to Detail - Define test case candidates for automation that are outside of product specifications. i.e. Negative Testing; Create thorough and accurate documentation of all work including status updates to summarize project highlights; validating that processes operate properly and conform to standards Automation - Automate defined test cases and test suites per project Collaboration - Collaborate with Product Owners and development team to plan and and assist with user acceptance testing; Collaborate with product owners, development leads and architects on functional and non-functional test strategies and plans Execution - Develop scalable and reliable automated tests; Develop performance testing scripts to assure products are adhering to the documented SLO/SLI/SLAs; Specify the need for Test Data types for automated testing; Create automated tests and tests data for projects; Develop automated regression suites; Integrate automated regression tests into the CI/CD pipeline; Work with teams on E2E testing strategies and plans against multiple product integration points Quality Control - Perform defect analysis, in-depth technical root cause analysis, identifying trends and recommendations to resolve complex functional issues and process improvements; Analyzes results of functional and non-functional tests and make recommendation for improvements; Performance / Resilience: Understanding application and network architecture as inputs to create performance and resilience test strategies and plans for each product and platform. Conducting the performance and resilience testing to ensure the products meet SLAs / SLOs Quality Focus - Review test cases for complete functional coverage; Review quality section of Production Readiness Review for completeness; Recommend changes to existing testing methodologies for effectiveness and efficiency of product validation; Ensure communications are thorough and accurate for all work documentation including status and project updates Risk Mitigation - Work with Product Owners, QE and development team leads to track and determine prioritization of defects fixes Show more Show less

Dear Job Seekers, Greetings from Voice Bay! We are currently hiring for Machine Learning Engineer , If you are interested, please submit your application. Please find below the JD for your consideration: Work Location – Hyderabad Exp – 4 – 10 Years Work Mode – 5 Days Work From Office Mandatory Key Responsibilities  Design, develop, and implement end-to-end machine learning models, from initial data exploration and feature engineering to model deployment and monitoring in production environments.  Build and optimize data pipelines for both structured and unstructured datasets, focusing on advanced data blending, transformation, and cleansing techniques to ensure data quality and readiness for modeling.  Create, manage, and query complex databases, leveraging various data storage solutions to efficiently extract, transform, and load data for machine learning workflows.  Collaborate closely with data scientists, software engineers, and product managers to translate business requirements into effective, scalable, and maintainable ML solutions.  Implement and maintain robust MLOps practices, including version control, model monitoring, logging, and performance evaluation to ensure model reliability and drive continuous improvement.  Research and experiment with new machine learning techniques, tools, and technologies to enhance our predictive capabilities and operational efficiency. Required Skills & Experience  5+ years of hands-on experience in building, training, and deploying machine learning models in a professional, production-oriented setting.  Demonstrable experience with database creation and advanced querying (e.g., SQL, NoSQL), with a strong understanding of data warehousing concepts.  Proven expertise in data blending, transformation, and feature engineering, adept at integrating and harmonizing both structured (e.g., relational databases, CSVs) and unstructured (e.g., text, logs, images) data.  Strong practical experience with cloud platforms for machine learning development and deployment; significant experience with Google Cloud Platform (GCP) services (e.g., Vertex AI, BigQuery, Dataflow) is highly desirable.  Proficiency in programming languages commonly used in data science (e.g., Python is preferred, R).  Solid understanding of various machine learning algorithms (e.g., regression, classification, clustering, dimensionality reduction) and experience with advanced techniques like Deep Learning, Natural Language Processing (NLP), or Computer Vision.  Experience with machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch).  Familiarity with MLOps tools and practices, including model versioning, monitoring, A/B testing, and continuous integration/continuous deployment (CI/CD) pipelines.  Experience with containerization technologies like Docker and orchestration tools like Kubernetes for deploying ML models as REST APIs.  Proficiency with version control systems (e.g., Git, GitHub/GitLab) for collaborative development. Educational Background  Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Engineering, Data Science, or a closely related quantitative field.  Alternatively, a significant certification in Data Science, Machine Learning, or Cloud AI combined with relevant practical experience will be considered.  A compelling combination of relevant education and professional experience will also be valued. Interested Candidates can share their Resume to the below mentioned Email I.D tarunrai@voicebaysolutions.in hr@voicebaysolutions.in Show more Show less