365 Athena Jobs - Page 11

Roles and responsibilities Work closely with the Product Owners and stake holders to design the Technical Architecture for data platform to meet the requirements of the proposed solution. Work with the leadership to set the standards for software engineering practices within the machine learning engineering team and support across other disciplines Play an active role in leading team meetings and workshops with clients. Choose and use the right analytical libraries, programming languages, and frameworks for each task. Help the Data Engineering team produce high-quality code that allows us to put solutions into production Create and own the technical product backlogs for products, help the team to close the backlogs in right time. Refactor code into reusable libraries, APIs, and tools. Help us to shape the next generation of our products. What Were Looking For Total experience in data management area for 10 + years’ experience in the implementation of modern data ecosystems in AWS/Cloud platforms. Strong experience with AWS ETL/File Movement tools (GLUE, Athena, Lambda, Kinesis and other AWS integration stack) Strong experience with Agile Development, SQL Strong experience with Two or Three AWS database technologies (Redshift, Aurora, RDS,S3 & other AWS Data Service ) covering security, policies, access management Strong programming Experience with Python and Spark Strong learning curve for new technologies Experience with Apache Airflow & other automation stack. Excellent with Data Modeling. Excellent oral and written communication skills. A high level of intellectual curiosity, external perspective, and innovation interest Strong analytical, problem solving and investigative skills Experience in applying quality and compliance requirements. Experience with security models and development on large data sets

Role & responsibilities Essential Skills: Experience: 6 to 10 yrs - Technical Expertise: Proficiency in AWS services such as Amazon S3, Redshift, EMR, Glue, Lambda, and Kinesis. Strong skills in SQL and experience with scripting languages like Python or Java. - Data Engineering Experience: Hands on experience in building and maintaining data pipelines, data modeling, and working with big data technologies. - Problem-Solving Skills: Ability to analyze complex data issues and develop effective solutions to optimize data processing and storage. - Communication and Collaboration: Strong interpersonal skills to work effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders. Educational Qualifications A bachelor's degree in computer science, information technology, or a related field is typically required. Relevant AWS certifications, such as AWS Certified Data Analytics Specialty, are advantageous

Develop and implement efficient data pipelines using Apache Spark (PySpark preferred) to process and analyze large-scale data. Design, build, and optimize complex SQL queries to extract, transform, and load (ETL) data from multiple sources. Orchestrate data workflows using Apache Airflow , ensuring smooth execution and error-free pipelines. Design, implement, and maintain scalable and cost-effective data storage and processing solutions on AWS using S3, Glue, EMR, and Athena . Leverage AWS Lambda and Step Functions for serverless compute and task orchestration in data pipelines. Work with AWS databases like RDS and DynamoDB to ensure efficient data storage and retrieval. Monitor data processing and pipeline health using AWS CloudWatch and ensure smooth operation in production environments. Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver solutions. Perform performance tuning, optimize distributed data processing tasks, and handle scalability issues. Provide troubleshooting and support for data pipeline failures and ensure high availability and reliability. Contribute to the setup and maintenance of CI/CD pipelines for automated deployment and testing of data workflows. Required Skills & Experience : Experience: Minimum of 6+ years of hands-on experience in data engineering or big data development roles, with a focus on designing and building data pipelines and processing systems. Technical Skills: Strong programming skills in Python with hands-on experience in Apache Spark (PySpark preferred). Proficient in writing and optimizing complex SQL queries for data extraction, transformation, and loading. Hands-on experience with Apache Airflow for orchestration of data workflows and pipeline management. In-depth understanding and practical experience with AWS services : Data Storage & Processing: S3, Glue, EMR, Athena Compute & Execution: Lambda, Step Functions Databases: RDS, DynamoDB Monitoring: CloudWatch Experience with distributed data processing, parallel computing, and performance tuning techniques. Strong analytical and problem-solving skills to troubleshoot and optimize data workflows and pipelines. Familiarity with CI/CD pipelines and DevOps practices for continuous integration and automated deployments is a plus. Preferred Qualifications: Familiarity with other cloud platforms (Azure, Google Cloud) and services related to data engineering. Experience in handling unstructured and semi-structured data and working with data lakes. Knowledge of containerization technologies such as Docker or orchestration systems like Kubernetes . Experience with NoSQL databases or data warehouses like Redshift or BigQuery is a plus. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. Experience: Minimum of 6+ years in a data engineering role with strong expertise in AWS and big data processing frameworks.

We are currently seeking a Data Visualization Expert - Quick sight to join our team in Chennai, Tamil Ndu (IN-TN), India (IN). What awaits you/ Job Profile Location Bangalore and Chennai, Hybrid mode,Immediate to 10 Days Notice period Develop reports using Amazon Quicksight Data Visualization DevelopmentDesign and develop data visualizations using Amazon Quicksight to present complex data in a clear and understandable format. Create interactive dashboards and reports that allow end-users to explore data and draw meaningful conclusions. Data AnalysisCollaborate with data analysts and business stakeholders to understand data requirements, gather insights, and transform raw data into actionable visualizations. Dashboard User Interface (UI) and User Experience (UX)Ensure that the data visualizations are user-friendly, intuitive, and aesthetically pleasing. Optimize the user experience by incorporating best practices in UI/UX design. Data IntegrationWork closely with data engineers and data architects to ensure seamless integration of data sources into Quicksight, enabling real-time and up-to-date visualizations. Performance OptimizationIdentify and address performance bottlenecks in data queries and visualization rendering to ensure quick and responsive dashboards. Data Security and GovernanceEnsure compliance with data security policies and governance guidelines when handling sensitive data within Quicksight. Training and DocumentationProvide training and support to end-users and stakeholders on how to interact with and interpret visualizations effectively. Create detailed documentation of the visualization development process. Stay Updated with Industry TrendsKeep up to date with the latest data visualization trends, technologies, and best practices to continuously enhance the quality and impact of visualizations. Using the Agile Methodology, attending daily standups and use of the Agile tools Collaborating with cross-functional teams and stakeholders to ensure data security, privacy, and compliance with regulations. using Scrum/Kanban Proficiency in Software Development best practices - Secure coding standards, Unit testing frameworks, Code coverage, Quality gates. Ability to lead and deliver change in a very productive way Lead Technical discussions with customers to find the best possible solutions. W orking closely with the Project Manager, Solution Architect and managing client communication (as and when required) What should you bring along Must Have Person should have relevant work experience in analytics, reporting and business intelligence tools. 4-5 years of hands-on experience in data visualization. Relatively 2-year Experience developing visualization using Amazon Quicksight. Experience working with various data sources and databases. Ability to work with large datasets and design efficient data models for visualization. Nice to Have AI Project implementation and AI methods. Must have technical skill Quick sight , SQL , AWS Good to have Technical skills Tableau, Data Engineer

We are currently seeking a Data Visualization Expert - Quick sight to join our team in Chennai, Tamil Ndu (IN-TN), India (IN). What awaits you/ Job Profile Design and develop data visualizations using Amazon QuickSight to present complex data in clear and understandable Dashboards. Create interactive dashboards and reports that allow end-users to explore data and draw meaningful conclusions. Work on Data preparation and ensure the good quality data is used in Visualization. Collaborate with data analysts and business stakeholders to understand data requirements, gather insights, and transform raw data into actionable visualizations. Ensure that the data visualizations are user-friendly, intuitive, and aesthetically pleasing. Optimize the user experience by incorporating best practices. Identify and address performance bottlenecks in data queries and visualization. Ensure compliance with data security policies and governance guidelines when handling sensitive data within QuickSight. Provide training and support to end-users and stakeholders on how to interact with Dashboards. Self-Managing and explore the latest technical development and incorporate in the project. Experience in analytics, reporting and business intelligence tools. Using the Agile Methodology, attending daily standups and use of the Agile tools. Lead Technical discussions with customers to find the best possible solutions. What should you bring along Must Have Overall experience of 2-5 years in Data visualization development. Minimum of 2 years in QuickSight and 1-2 years in other BI Tools like Tableau, PowerBI, Qlik Good In writing complex SQL Scripting, Dataset Modeling. Hands on in AWS -Athena, RDS, S3, IAM, permissions, Logging and monitoring Services. Experience working with various data sources and databases like Oracle, mySQL, S3, Athena. Ability to work with large datasets and design efficient data models for visualization. Prior experience in working in Agile, Scrum/Kanban working model. Nice to Have Knowledge on Data ingestion and Data pipeline in AWS. Knowledge Amazon Q or AWS LLM Service to enable AI integration Must have skill Quick sight, Tableau, SQL , AWS Good to have skills Qlikview ,Data Engineer, AWS LLM

Must-Have Qualifications: AWS Expertise: Strong hands-on experience with AWS data services including Glue, Redshift, Athena, S3, Lake Formation, Kinesis, Lambda, Step Functions, EMR , and CloudWatch . ETL/ELT Engineering: Deep proficiency in designing robust ETL/ELT pipelines with AWS Glue (PySpark/Scala), Python, dbt , or other automation frameworks. Data Modeling: Advanced knowledge of dimensional (Star/Snowflake) and normalised data modeling, optimised for Redshift and S3-based lakehouses . Programming Skills: Proficient in Python, SQL, and PySpark , with automation and scripting skills for data workflows. Architecture Leadership: Demonstrated experience leading large-scale AWS data engineering projects across teams and domains. Pre-sales & Consulting: Proven experience working with clients, responding to technical RFPs, and designing cloud-native data solutions. Advanced PySpark Expertise: Deep hands-on experience in writing optimized PySpark code for distributed data processing, including transformation pipelines using DataFrames , RDDs , and Spark SQL , with a strong grasp of lazy evaluation , catalyst optimizer , and Tungsten execution engine . Performance Tuning & Partitioning: Proven ability to debug and optimize Spark jobs through custom partitioning strategies , broadcast joins , caching , and checkpointing , with proficiency in tuning executor memory , shuffle configurations , and leveraging Spark UI for performance diagnostics in large-scale data workloads (>TB scale).

Role Overview In this role, you'll work in one of our IBM Consulting Client Innovation Centers (Delivery Centers) , where we deliver deep technical and industry expertise to a wide range of public and private sector clients around the world. Our delivery centers offer our clients locally based skills and technical expertise to drive innovation and adoption of new technology. Your Role and Responsibilities Data Strategy and Planning : Develop and implement data architecture strategies that align with organizational goals and objectives. Collaborate with business stakeholders to understand data requirements and translate them into actionable plans. Data Modeling : Design and implement logical and physical data models to support business needs. Ensure data models are scalable, efficient, and comply with industry best practices. Database Design and Management : Oversee the design and management of databases, selecting appropriate database technologies based on requirements. Optimize database performance and ensure data integrity and security. Data Integration : Define and implement data integration strategies to facilitate seamless flow of information across systems. Responsibilities: Experience in data architecture and engineering. Proven expertise with Snowflake data platform . Strong understanding of ETL/ELT processes and data integration . Experience with data modeling and data warehousing concepts. Familiarity with performance tuning and optimization techniques. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills. Required Education Bachelor's Degree Preferred Education Master's Degree Required Technical and Professional Expertise Cloud & Data Architecture : AWS, Snowflake ETL & Data Engineering : AWS Glue, Apache Spark, Step Functions Big Data & Analytics : Athena, Presto, Hadoop Database & Storage : SQL, Snow SQL Security & Compliance : IAM, KMS, Data Masking Preferred Technical and Professional Experience Cloud Data Warehousing : Snowflake (Data Modeling, Query Optimization) Data Transformation : DBT (Data Build Tool) for ELT pipeline management Metadata & Data Governance : Alation (Data Catalog, Lineage, Governance)

Who We Are At Kyndryl, we design, build, manage and modernize the mission-critical technology systems that the world depends on every day. So why work at Kyndryl? We are always moving forward – always pushing ourselves to go further in our efforts to build a more equitable, inclusive world for our employees, our customers and our communities. The Role Are you ready to dive headfirst into the captivating world of data engineering at Kyndryl? As a Data Engineer, you'll be the visionary behind our data platforms, crafting them into powerful tools for decision-makers. Your role? Ensuring a treasure trove of pristine, harmonized data is at everyone's fingertips. AWS Data/API Gateway Pipeline Engineer responsible for designing, building, and maintaining real-time, serverless data pipelines and API services. This role requires extensive hands-on experience with Java, Python, Redis, DynamoDB Streams, and PostgreSQL, along with working knowledge of AWS Lambda and AWS Glue for data processing and orchestration. This position involves collaboration with architects, backend developers, and DevOps engineers to deliver scalable, event-driven data solutions and secure API services across cloud-native systems. Key Responsibilities API & Backend Engineering Build and deploy RESTful APIs using AWS API Gateway, Lambda, and Java and Python. Integrate backend APIs with Redis for low-latency caching and pub/sub messaging. Use PostgreSQL for structured data storage and transactional processing. Secure APIs using IAM, OAuth2, and JWT, and implement throttling and versioning strategies. Data Pipeline & Streaming Design and develop event-driven data pipelines using DynamoDB Streams to trigger downstream processing. Use AWS Glue to orchestrate ETL jobs for batch and semi-structured data workflows. Build and maintain Lambda functions to process real-time events and orchestrate data flows. Ensure data consistency and resilience across services, queues, and databases. Cloud Infrastructure & DevOps Deploy and manage cloud infrastructure using CloudFormation, Terraform, or AWS CDK. Monitor system health and service metrics using CloudWatch, SNS and structured logging. Contribute to CI/CD pipeline development for testing and deploying Lambda/API services. So, if you're a technical enthusiast with a passion for data, we invite you to join us in the exhilarating world of data engineering at Kyndryl. Let's transform data into a compelling story of innovation and growth. Your Future at Kyndryl Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won’t find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here. Who You Are You’re good at what you do and possess the required experience to prove it. However, equally as important – you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused – someone who prioritizes customer success in their work. And finally, you’re open and borderless – naturally inclusive in how you work with others. Required Skills and Experience Bachelor's degree in computer science, Engineering, or a related field. Over 6 years of experience in developing backend or data pipeline services using Java and Python . Strong hands-on experience with: AWS API Gateway , Lambda , DynamoDB Streams Redis (caching, messaging) PostgreSQL (schema design, tuning, SQL) AWS Glue for ETL jobs and data transformation Solid understanding of REST API design principles, serverless computing, and real-time architecture. Preferred Skills and Experience Familiarity with Kafka, Kinesis, or other message streaming systems Swagger/OpenAPI for API documentation Docker and Kubernetes (EKS) Git, CI/CD tools (e.g., GitHub Actions) Experience with asynchronous event processing, retries, and dead-letter queues (DLQs) Exposure to data lake architectures (S3, Glue Data Catalog, Athena) Being You Diversity is a whole lot more than what we look like or where we come from, it’s how we think and who we are. We welcome people of all cultures, backgrounds, and experiences. But we’re not doing it single-handily: Our Kyndryl Inclusion Networks are only one of many ways we create a workplace where all Kyndryls can find and provide support and advice. This dedication to welcoming everyone into our company means that Kyndryl gives you – and everyone next to you – the ability to bring your whole self to work, individually and collectively, and support the activation of our equitable culture. That’s the Kyndryl Way. What You Can Expect With state-of-the-art resources and Fortune 100 clients, every day is an opportunity to innovate, build new capabilities, new relationships, new processes, and new value. Kyndryl cares about your well-being and prides itself on offering benefits that give you choice, reflect the diversity of our employees and support you and your family through the moments that matter – wherever you are in your life journey. Our employee learning programs give you access to the best learning in the industry to receive certifications, including Microsoft, Google, Amazon, Skillsoft, and many more. Through our company-wide volunteering and giving platform, you can donate, start fundraisers, volunteer, and search over 2 million non-profit organizations. At Kyndryl, we invest heavily in you, we want you to succeed so that together, we will all succeed. Get Referred! If you know someone that works at Kyndryl, when asked ‘How Did You Hear About Us’ during the application process, select ‘Employee Referral’ and enter your contact's Kyndryl email address.

Roles and Responsibilities: Experience in GLUE AWS Experience with one or more of the followingSpark, Scala, Python, and/or R . Experience in API development with NodeJS Experience with AWS (S3, EC2) or other cloud provider Experience in Data Virtualization tools like Dremio and Athena is a plus Should be technically proficient in Big Data concepts Should be technically proficient in Hadoop and noSQL (MongoDB) Good communication and documentation skills

8+ years experience combined between backend and data platform engineering roles Worked on large scale distributed systems. 5+ years of experience building data platform with (one of) Apache Spark, Flink or with similar frameworks. 7+ years of experience programming with Java Experience building large scale data/event pipelines Experience with relational SQL and NoSQL databases, including Postgres/MySQL, Cassandra, MongoDB Demonstrated experience with EKS, EMR, S3, IAM, KDA, Athena, Lambda, Networking, elastic cache and other AWS services.

PySpark, Python, SQL Strong focus on big data processing,which is core to data engineering. AWS Cloud Services (Lambda, Glue, S3, IAM) Indicates working with cloud-based data pipelines. Airflow, GitHub Essential for orchestration and version control in data workflows.

3+ years of experience in data science roles, working with tabular data in large-scale projects. Experience in feature engineering and working with methods such as XGBoost, LightGBM, factorization machines , and similar algorithms. Experience in adtech or fintech industries is a plus. Familiarity with clickstream data, predictive modeling for user engagement, or bidding optimization is highly advantageous. MS or PhD in mathematics, computer science, physics, statistics, electrical engineering, or a related field. Proficiency in Python (3.9+), with experience in scientific computing and machine learning tools (e.g., NumPy, Pandas, SciPy, scikit-learn, matplotlib, etc.). Familiarity with deep learning frameworks (such as TensorFlow or PyTorch) is a plus. Strong expertise in applied statistical methods, A/B testing frameworks, advanced experiment design, and interpreting complex experimental results. Experience querying and processing data using SQL and working with distributed data storage solutions (e.g., AWS Redshift, Snowflake, BigQuery, Athena, Presto, MinIO, etc.). Experience in budget allocation optimization, lookalike modeling, LTV prediction, or churn analysis is a plus. Ability to manage multiple projects, prioritize tasks effectively, and maintain a structured approach to complex problem-solving. Excellent communication and collaboration skills to work effectively with both technical and business teams.

To Apply - Submit Details via Google Form - https://forms.gle/8SUxUV2cikzjvKzD9 As a Senior Consultant in our Consulting team, youll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations Seeking experienced AWS Data Engineers to design, implement, and maintain robust data pipelines and analytics solutions using AWS services. The ideal candidate will have a strong background in AWS data services, big data technologies, and programming languages. Role & responsibilities 1. Design and implement scalable, high-performance data pipelines using AWS services 2. Develop and optimize ETL processes using AWS Glue, EMR, and Lambda 3. Build and maintain data lakes using S3 and Delta Lake 4. Create and manage analytics solutions using Amazon Athena and Redshift 5. Design and implement database solutions using Aurora, RDS, and DynamoDB 6. Develop serverless workflows using AWS Step Functions 7. Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL 8. Ensure data quality, security, and compliance with industry standards 9. Collaborate with data scientists and analysts to support their data needs 10. Optimize data architecture for performance and cost-efficiency 11. Troubleshoot and resolve data pipeline and infrastructure issues Preferred candidate profile 1. Bachelors degree in computer science, Information Technology, or related field 2. Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS 3. Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S3 4. Experience with data lake technologies, particularly Delta Lake 5. Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL 6. Proficiency in Python and PySpark programming 7. Strong SQL skills and experience with PostgreSQL 8. Experience with AWS Step Functions for workflow orchestration Technical Skills: - AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB , Step Functions - Big Data: Hadoop, Spark, Delta Lake - Programming: Python, PySpark - Databases: SQL, PostgreSQL, NoSQL - Data Warehousing and Analytics - ETL/ELT processes - Data Lake architectures - Version control: Git - Agile methodologies

To Apply - Submit Details via Google Form - https://forms.gle/8SUxUV2cikzjvKzD9 As a Senior Consultant in our Consulting team, youll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations Seeking experienced AWS Data Engineers to design, implement, and maintain robust data pipelines and analytics solutions using AWS services. The ideal candidate will have a strong background in AWS data services, big data technologies, and programming languages. Role & responsibilities 1. Design and implement scalable, high-performance data pipelines using AWS services 2. Develop and optimize ETL processes using AWS Glue, EMR, and Lambda 3. Build and maintain data lakes using S3 and Delta Lake 4. Create and manage analytics solutions using Amazon Athena and Redshift 5. Design and implement database solutions using Aurora, RDS, and DynamoDB 6. Develop serverless workflows using AWS Step Functions 7. Write efficient and maintainable code using Python/PySpark, and SQL/PostgrSQL 8. Ensure data quality, security, and compliance with industry standards 9. Collaborate with data scientists and analysts to support their data needs 10. Optimize data architecture for performance and cost-efficiency 11. Troubleshoot and resolve data pipeline and infrastructure issues Preferred candidate profile 1. Bachelors degree in computer science, Information Technology, or related field 2. Relevant years of experience as a Data Engineer, with at least 60% of experience focusing on AWS 3. Strong proficiency in AWS data services: Glue, EMR, Lambda, Athena, Redshift, S3 4. Experience with data lake technologies, particularly Delta Lake 5. Expertise in database systems: Aurora, RDS, DynamoDB, PostgreSQL 6. Proficiency in Python and PySpark programming 7. Strong SQL skills and experience with PostgreSQL 8. Experience with AWS Step Functions for workflow orchestration Technical Skills: - AWS Services: Glue, EMR, Lambda, Athena, Redshift, S3, Aurora, RDS, DynamoDB , Step Functions - Big Data: Hadoop, Spark, Delta Lake - Programming: Python, PySpark - Databases: SQL, PostgreSQL, NoSQL - Data Warehousing and Analytics - ETL/ELT processes - Data Lake architectures - Version control: Git - Agile methodologies

EPAM has presence across 40+ countries globally with 55,000 + professionals & numerous delivery centers, Key locations are North America, Eastern Europe, Central Europe, Western Europe, APAC, Mid East & Development Centers in India (Hyderabad, Pune & Bangalore). Location: Gurgaon/Pune/Hyderabad/Bengaluru/Chennai Work Mode: Hybrid (2-3 days office in a week) Job Description: 5-14 Years of in Big Data & Data related technology experience Expert level understanding of distributed computing principles Expert level knowledge and experience in Apache Spark Hands on programming with Python Proficiency with Hadoop v2, Map Reduce, HDFS, Sqoop Experience with building stream-processing systems, using technologies such as Apache Storm or Spark-Streaming Good understanding of Big Data querying tools, such as Hive, and Impala Experience with integration of data from multiple data sources such as RDBMS (SQL Server, Oracle), ERP, Files Good understanding of SQL queries, joins, stored procedures, relational schemas Experience with NoSQL databases, such as HBase, Cassandra, MongoDB Knowledge of ETL techniques and frameworks Performance tuning of Spark Jobs Experience with native Cloud data services AWS Ability to lead a team efficiently Experience with designing and implementing Big data solutions Practitioner of AGILE methodology WE OFFER Opportunity to work on technical challenges that may impact across geographies Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications Opportunity to share your ideas on international platforms Sponsored Tech Talks & Hackathons Possibility to relocate to any EPAM office for short and long-term projects Focused individual development Benefit package: • Health benefits, Medical Benefits• Retirement benefits• Paid time off• Flexible benefits Forums to explore beyond work passion (CSR, photography, painting, sports, etc

Your Role As a senior software engineer with Capgemini, you should have 4 + years of experience in Snowflake Data Engineer with strong project track record In this role you will play a key role in Strong customer orientation, decision making, problem solving, communication and presentation skills Very good judgement skills and ability to shape compelling solutions and solve unstructured problems with assumptions Very good collaboration skills and ability to interact with multi-cultural and multi-functional teams spread across geographies Strong executive presence andspirit Superb leadership and team building skills with ability to build consensus and achieve goals through collaboration rather than direct line authority Your Profile 4+ years of experience in data warehousing, and cloud data solutions. Minimum 2+ years of hands-on experience with End-to-end Snowflake implementation. Experience in developing data architecture and roadmap strategies with knowledge to establish data governance and quality frameworks within Snowflake Expertise or strong knowledge in Snowflake best practices, performance tuning, and query optimisation. Experience with cloud platforms like AWS or Azure and familiarity with Snowflakes integration with these environments. Strong knowledge in at least one cloud (AWS or Azure) is mandatory Skills (competencies) Ab Initio Agile (Software Development Framework) Apache Hadoop AWS Airflow AWS Athena AWS Code Pipeline AWS EFS AWS EMR AWS Redshift AWS S3 Azure ADLS Gen2 Azure Data Factory Azure Data Lake Storage Azure Databricks Azure Event Hub Azure Stream Analytics Azure Sunapse Bitbucket Change Management Client Centricity Collaboration Continuous Integration and Continuous Delivery (CI/CD) Data Architecture Patterns Data Format Analysis Data Governance Data Modeling Data Validation Data Vault Modeling Database Schema Design Decision-Making DevOps Dimensional Modeling GCP Big Table GCP BigQuery GCP Cloud Storage GCP DataFlow GCP DataProc Git Google Big Tabel Google Data Proc Greenplum HQL IBM Data Stage IBM DB2 Industry Standard Data Modeling (FSLDM) Industry Standard Data Modeling (IBM FSDM)) Influencing Informatica IICS Inmon methodology JavaScript Jenkins Kimball Linux - Redhat Negotiation Netezza NewSQL Oracle Exadata Performance Tuning Perl Platform Update Management Project Management PySpark Python R RDD Optimization SantOs SaS Scala Spark Shell Script Snowflake SPARK SPARK Code Optimization SQL Stakeholder Management Sun Solaris Synapse Talend Teradata Time Management Ubuntu Vendor Management

Your Role As a senior software engineer with Capgemini, you should have 4 + years of experience in Azure Data Engineer with strong project track record In this role you will play a key role in Strong customer orientation, decision making, problem solving, communication and presentation skills Very good judgement skills and ability to shape compelling solutions and solve unstructured problems with assumptions Very good collaboration skills and ability to interact with multi-cultural and multi-functional teams spread across geographies Strong executive presence andspirit Superb leadership and team building skills with ability to build consensus and achieve goals through collaboration rather than direct line authority Your Profile Experience with Azure Data Bricks, Data Factory Experience with Azure Data components such as Azure SQL Database, Azure SQL Warehouse, SYNAPSE Analytics Experience in Python/Pyspark/Scala/Hive Programming. Experience with Azure Databricks/ADB Experience with building CI/CD pipelines in Data environments Primary Skills ADF (Azure Data Factory) OR ADB (Azure Data Bricks) Secondary Skills Excellent verbal and written communication and interpersonal skills Skills (competencies) Ab Initio Agile (Software Development Framework) Apache Hadoop AWS Airflow AWS Athena AWS Code Pipeline AWS EFS AWS EMR AWS Redshift AWS S3 Azure ADLS Gen2 Azure Data Factory Azure Data Lake Storage Azure Databricks Azure Event Hub Azure Stream Analytics Azure Sunapse Bitbucket Change Management Client Centricity Collaboration Continuous Integration and Continuous Delivery (CI/CD) Data Architecture Patterns Data Format Analysis Data Governance Data Modeling Data Validation Data Vault Modeling Database Schema Design Decision-Making DevOps Dimensional Modeling GCP Big Table GCP BigQuery GCP Cloud Storage GCP DataFlow GCP DataProc Git Google Big Tabel Google Data Proc Greenplum HQL IBM Data Stage IBM DB2 Industry Standard Data Modeling (FSLDM) Industry Standard Data Modeling (IBM FSDM)) Influencing Informatica IICS Inmon methodology JavaScript Jenkins Kimball Linux - Redhat Negotiation Netezza NewSQL Oracle Exadata Performance Tuning Perl Platform Update Management Project Management PySpark Python R RDD Optimization SantOs SaS Scala Spark Shell Script Snowflake SPARK SPARK Code Optimization SQL Stakeholder Management Sun Solaris Synapse Talend Teradata Time Management Ubuntu Vendor Management

Dear Candidate, We are pleased to invite you to participate in the EY GDS face to face hiring Event for the position of AWS Data Engineer. Role: AWS Data Engineer Experience Required: 5-8 Years Location - Hyderabad Mode of interview - Face to Face JD - Technical Skills: • Must have Strong experience in AWS Data Services like Glue , Lambda, Even bridge, Kinesis, S3/ EMR , Redshift , RDS, Step functions, Airflow & Pyspark • Strong exposure to IAM, Cloud Trail , Cluster optimization , Python & SQL • Should have expertise in Data design, STTM, understanding of Data models , Data component design, Automated testing, Code Coverage, UAT support , Deployment and go live • Experience with version control systems like SVN, Git. Create and manage AWS Glue crawlers and jobs to automate data cataloging and ingestion processes across various structured and unstructured data sources. • Strong experience with AWS Glue building ETL pipelines, managing crawlers, and working with Glue data catalogue. • Proficiency in AWS Redshift designing and managing Redshift clusters, writing complex SQL queries, and optimizing query performance. • Enable data consumption from reporting and analytics business applications using AWS services (ex: QuickSight, Sagemaker, JDBC / ODBC connectivity, etc.) Kindly confirm your availability by applying to this Job

W e are seeking a highly skilled , hands -on and technically proficient Test Automation Engineering Manager with strong experience in data quality , data integration , and a specific focus on semantic layer validation . This role combines technical ownership of automated data testing solutions with team leadership responsibilities, ensuring that the data infrastructure across platforms remains accurate , reliable, and high performing . As a leader in the QA and Data Engineering space, you will be responsible for building robust automated testing frameworks, validating GraphQL -based data layers, and driving the teams technical growth. Your work will ensure that all data flows, transformations, and API interactions meet enterprise-grade quality standards across the data lifecycle. Y ou will be responsible for the end-to-end design and development of test automation frameworks, working collaboratively with your team. As the delivery owner for test automation, your primary responsibilities will include building and automating comprehensive validation frameworks for semantic layer testing, GraphQL API validation, and schema compliance , ensuring alignment with data quality, performance, and integration reliability standards. You will also work closely with data engineers, product teams, and platform architects to validate data contracts and integration logic, supporting the integrity and trustworthiness of enterprise data solutions. This is a highly technical and hands-on role, with strong emphasis on automation, data workflow validation , and the seamless integration of testing practices into CI/CD pipelines . Roles & Responsibilities: Design and implement robust data validation frameworks focused on the semantic layer, ensuring accurate data model, schema compliance, and contract adherence across services and platforms. Build and automate end-to-end data pipeline validations across ingestion, transformation, and consumption layers using Databricks, Apache Spark, and AWS services such as S3, Glue, Athena, and Lake Formation. Lead test automation initiatives by developing scalable, modular test frameworks and embedding them into CI/CD pipelines for continuous validation of semantic models, API integrations, and data workflows. Validate GraphQL APIs by testing query/mutation structures, schema compliance, and end-to-end integration accuracy using tools like Postman, Python, and custom test suites. Oversee UI and visualization testing for tools like Tableau, Power BI, and custom front-end dashboards, ensuring consistency with backend data through Selenium with Python and backend validations. Define and drive the overall QA strategy with emphasis on performance, reliability, and semantic data accuracy, while setting up alerting and reporting mechanisms for test failures, schema issues, and data contract violations. Collaborate closely with product managers, data engineers, developers, and DevOps teams to align quality assurance initiatives with business goals and agile release cycles. Actively contribute to architecture and design discussions, ensuring quality and testability are embedded from the earliest stages of development. Mentor and manage QA engineers, fostering a collaborative environment focused on technical excellence, knowledge sharing, and continuous professional growth. Must-Have Skills: Team Leadership Experience is also required. Strong 6+ years of experience in Requested Data Ops/Testing is required 7+ to 12 years of Overall experience is expected in Test Automation. Strong experience in designing and implementing test automation frameworks integrated with CI/CD pipelines. Expertise in validating data pipelines at the syntactic layer, including schema checks, null/duplicate handling, and transformation validation. Hands-on experience with Databricks, Apache Spark, and AWS services (S3, Glue, Athena, Lake Formation). Proficiency in Python, PySpark, and SQL for writing validation scripts and automation logic. Solid understanding of GraphQL APIs, including schema validation and query/mutation testing. Experience with API testing tools like Postman and Python-based test frameworks. Proficient in UI and visualization testing using Selenium with Python, especially for tools like Tableau, Power BI, or custom dashboards. Familiarity with CI/CD tools such as Jenkins, GitHub Actions, or GitLab CI for test orchestration. Ability to implement alerting and reporting for test failures, anomalies, and validation issues. Strong background in defining QA strategies and leading test automation initiatives in data-centric environments. Excellent collaboration and communication skills, with the ability to work closely with cross-functional teams in Agile settings. Mentor and manage QA engineers, fostering a collaborative environment focused on technical excellence, knowledge sharing, and continuous professional growth. Good-to-Have Skills: Experience with data governance tools such as Apache Atlas, Collibra, or Alation Understanding of DataOps methodologies and practices Contributions to internal quality dashboards or data observability systems Awareness of metadata-driven testing approaches and lineage-based validations Experience working with agile Testing methodologies such as Scaled Agile. Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest. Education and Professional Certifications Bachelors/Masters degree in computer science and engineering preferred. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills. EQUAL OPPORTUNITY STATEMENT We provide reasonable accommodations for individuals with disabilities during the application, interview process, job functions, and employment benefits. Contact us to request an accommodation .

ABOUT THE ROLE We are seeking a highly skilled, hands-on Senior QA & Test Automation Specialist ( T e st Automation Engineer ) with strong experience in data validation , ETL testing , test automation , and QA process ownership . This role combines deep technical execution with a solid foundation in QA best practices including test planning, defect tracking, and test lifecycle management . You will be responsible for designing and executing manual and automated test strategies for complex real-time and batch data pipelines , contributing to the design of automation frameworks , and ensuring high-quality data delivery across our AWS and Databricks-based analytics platforms . The role is highly technical and hands-on , with a strong focus on automation, metadata validation , and ensuring data governance practices are seamlessly integrated into development pipelines. Roles & Responsibilities: Collaborate with the QA Manager to design and implement end-to-end test strategies for data validation, semantic layer testing, and GraphQL API validation. Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification. Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines. Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection. Validate semantic layers (e.g., Looker, dbt models) and GraphQL APIs, ensuring data consistency, compliance with contracts, and alignment with business expectations. Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data. Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution. Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices. Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption. Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture. Experience building or maintainingtest data generators Contributions to internal quality dashboards or data observability systems Awareness of metadata-driven testing approaches and lineage-based validations Experience working with agile Testing methodologies such as Scaled Agile. Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest. Must-Have Skills: 6-9 years of experience in QA roles, with at least 3+ yearsof strong exposure to data pipeline testing and ETL validation. Strong in SQL, Python, and optionally PySpark comfortable with writing complex queries and validation scripts. Practical experience with manual validation of data pipelines and source-to-target testing. Experience in validating GraphQL APIs, semantic layers (Looker, dbt, etc.), and schema/data contract compliance. Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Athena, or BigQuery. Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentation. Experience working in Agile/Scrum environments with standard QA processes. Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr). Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management. Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validation. Proven experience in manual and automated testing of batch and real-time data pipelines. Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift). Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyr. Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysis. Experience integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions). Experience validating data from various file formats such as JSON, CSV, Parquet, and Avro Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validation Hands-on experience with API testing using Postman, pytest, or custom automation scripts Good-to-Have Skills: Experience with data governance tools such as Apache Atlas, Collibra, or Alation Familiarity with monitoring/observability tools such as Datadog, Prometheus, or CloudWatch Education and Professional Certifications Bachelors/Masters degree in computer science and engineering preferred. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.

Role Description: We are seeking a highly skilled, hands-on Senior QA & Test Automation Specialist (Test Automation Engineer)with strong experience in data validation , ETL testing , test automation , and QA process ownership . This role combines deep technical execution with a solid foundation in QA best practices including test planning, defect tracking, and test lifecycle management . You will be responsible for designing and executing manual and automated test strategies for complex real-time and batch data pipelines , contributing to the design of automation frameworks , and ensuring high-quality data delivery across our AWS and Databricks-based analytics platforms . The role is highly technical and hands-on , with a strong focus on automation, metadata validation , and ensuring data governance practices are seamlessly integrated into development pipelines. Roles & Responsibilities: Collaborate with the QA Manager to design and implement end-to-end test strategies for data validation, semantic layer testing, and GraphQL API validation. Perform manual validation of data pipelines, including source-to-target data mapping, transformation logic, and business rule verification. Develop and maintain automated data validation scripts using Python and PySpark for both real-time and batch pipelines. Contribute to the design and enhancement of reusable automation frameworks, with components for schema validation, data reconciliation, and anomaly detection. Validate semantic layers (e.g., Looker, dbt models) and GraphQL APIs, ensuring data consistency, compliance with contracts, and alignment with business expectations. Write and manage test plans, test cases, and test data for structured, semi-structured, and unstructured data. Track, manage, and report defects using tools like JIRA, ensuring thorough root cause analysis and timely resolution. Collaborate with Data Engineers, Product Managers, and DevOps teams to integrate tests into CI/CD pipelines and enable shift-left testing practices. Ensure comprehensive test coverage for all aspects of the data lifecycle, including ingestion, transformation, delivery, and consumption. Participate in QA ceremonies (standups, planning, retrospectives) and continuously contribute to improving the QA process and culture. Experience building or maintaining test data generators Contributions to internal quality dashboards or data observability systems Awareness of metadata-driven testing approaches and lineage-based validations Experience working with agile Testing methodologies such as Scaled Agile. Familiarity with automated testing frameworks like Selenium, JUnit, TestNG, or PyTest. Must-Have Skills: 69 years of experience in QA roles, with at least 3+ years of strong exposure to data pipeline testing and ETL validation. Strong in SQL, Python, and optionally PySpark comfortable with writing complex queries and validation scripts. Practical experience with manual validation of data pipelines and source-to-target testing. Experience in validating GraphQL APIs, semantic layers (Looker, dbt, etc.), and schema/data contract compliance. Familiarity with data integration tools and platforms such as Databricks, AWS Glue, Redshift, Athena, or BigQuery. Strong understanding of test planning, defect tracking, bug lifecycle management, and QA documentation. Experience working in Agile/Scrum environments with standard QA processes. Knowledge of test case and defect management tools (e.g., JIRA, TestRail, Zephyr). Strong understanding of QA methodologies, test planning, test case design, and defect lifecycle management. Deep hands-on expertise in SQL, Python, and PySpark for testing and automating validation. Proven experience in manual and automated testing of batch and real-time data pipelines. Familiarity with data processing and analytics stacks: Databricks, Spark, AWS (Glue, S3, Athena, Redshift). Experience with bug tracking and test management tools like JIRA, TestRail, or Zephyr. Ability to troubleshoot data issues independently and collaborate with engineering for root cause analysis. Experience integrating automated tests into CI/CD pipelines (e.g., Jenkins, GitHub Actions). Experience validating data from various file formats such as JSON, CSV, Parquet, and Avro Strong ability to validate and automate data quality checks: schema validation, null checks, duplicates, thresholds, and transformation validation Hands-on experience with API testing using Postman, pytest, or custom automation scripts Good-to-Have Skills: Experience with data governance tools such as Apache Atlas, Collibra, or Alation Familiarity with monitoring/observability tools such as Datadog, Prometheus, or Cloud Watch Education and Professional Certifications Bachelors/Masters degree in computer science and engineering preferred. Soft Skills: Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals Strong presentation and public speaking skills.

Director - Portfolio Operations Delivery What you will do Let’s do this. Let’s change the world. In this vital role the Director, Portfolio Effectiveness and Optimization Results Delivery within the Customer Data & Analytics team is accountable for coordinating our delivery efforts across the internal and external team located in AIN and across India. In addition, the Director must manage relationships across a complex internal set of teams and functional groups. This position reports to the Associate Vice President, Portfolio Effectiveness and Optimization and will be responsible for the following Responsibilities Key IntegratorAct as main point of contact and representative of the Portfolio Effectiveness and Optimization team in India Talent DevelopmentHire, train, develop, and manage talent to meet organizational needs Global CollaborationAct as the primary point of contact for PE&O senior leadership in the US and the offshore team in India, either through our Contract teams or direct AIN FTEs Operational Excellence and DeliveryOversee end-to-end delivery of core data and analytics projects ensuring quality, scalability, and operational efficiency, while promoting standard processes in data governance and analytics methodologies Offshore Vendor ManagementManage offshore teams including CWs, maintaining quality of service and timely deliverables Innovation LeadershipFoster a culture of innovation, ensuring the India team remains at the forefront of emerging technologies and trends in analytics, AI Business Impact & Collaborator ManagementEnsure analytics solutions drive tangible business outcomes and collaborate with global key collaborators to refine requirements, measure impact, and report progress Financial managementOversee PE&O budget associated with offshore work in India, ensuring best negotiated rates and overall value What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate degree and 4 years of statistics, operations research, mathematics, econometrics, business administration or a quantitative field experience OR Master’s degree and 14 to 16 years of statistics, operations research, mathematics, econometrics, business administration or a quantitative field experience OR Bachelor’s degree and 16 to 18 years of statistics, operations research, mathematics, econometrics, business administration or a quantitative field experience Managerial experience, directly handling people and/or leadership experience leading teams, projects, programs or directing the allocation of resources Preferred Qualifications: Relevant data science certifications and Bio/Pharmaceutical industry experience 8+ years of innovative Data Science/Advanced Analytics leadership experience Experience in AI, Machine Learning, quantitative methods, multivariate statistics, predictive modelling and other analytics frameworks/techniques with 10+ years of experience delivering complex analytical projects Minimum 5 years of professional experience in Amazon Web ServicesRedShift, S3, Athena, etc. and industry standard Data Warehousing technologiesSnowflake, Spark, Airflow, etc. Advanced proficiency and hands on coding experience in Python/R/Scala/Java or any other Object-Oriented Programming language; ETL using SQL/shell scripting Experience in successfully completing AI/ML based Next Best Action recommendation engine to optimize against desired objective function(s) Expertise in setting up and measuring randomized controlled trials, cohort studies, and matched, case-control studies Comprehensive understanding of the components of setting up data models and running scenario planning that match the business need Experience in setting up process for data ingestion, Quality Checks etc. Thorough understanding of tagging, Google Analytics, CRM, Content Management Systems, and other components of a Digital Marketing Ecosystem. Leadership experience in building and developing dedication teams, delivering results, and shaping the future Ability to foster and encourage an environment of openness and transparency in seeking diverse opinions and empower risk-taking in idea generation, idea incubation and/or experimentation The ideal candidate will lead the creation of an analytics-driven culture that drives top-line growth, controls costs, and takes timely corrective action to reduce risks that derail plans Ability to think strategically about issues impacting an entire portfolio of therapeutics across geographies and stages of development Experience managing multiple senior key collaborators, prioritizing across a multitude of responsibilities and allocating resources to drive maximum impact Partners with business leaders to deliver high-quality predictions that guide strategic decision making Oral, written and presentation skills to explain complex concepts and controversial findings clearly to a variety of audiences, including senior management Comfortable challenging the status quo and bringing forward innovative solutions Ability to identify areas for process and systems innovation and implement change that will enhance the overall effectiveness of the team Comfortable working through and leading large-scale global change management Understanding of technology platforms and ability to partner with IS/IT and business leaders What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now and make a lasting impact with the Amgen team. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

What you will do Let’s do this. Let’s change the world. In this vital role you will be responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and driving data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes Roles & Responsibilities: Design, develop, and maintain data solutions for data generation, collection, and processing Be a key team member that assists in design and development of the data pipeline Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks Collaborate with multi-functional teams to understand data requirements and design solutions that meet business needs Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency Implement data security and privacy measures to protect sensitive data Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions Collaborate and communicate effectively with product teams Collaborate with Data Architects, Business SMEs, and Data Scientists to design and develop end-to-end data pipelines to meet fast paced business needs across geographic regions Identify and resolve complex data-related challenges Adhere to standard methodologies for coding, testing, and designing reusable code/component Explore new tools and technologies that will help to improve ETL platform performance Participate in sprint planning meetings and provide estimations on technical implementation What we expect of you We are all different, yet we all use our unique contributions to serve patients. Basic Qualifications: Doctorate degree OR Master’s degree and 4 to 6 years of Computer Science, IT or related field OR Bachelor’s degree and 6 to 8 years of Computer Science, IT or related field OR Diploma and 10 to 12 years of Computer Science, IT or related field Preferred Qualifications: Functional Skills: Must-Have Skills Proficiency in Python, PySpark, and Scala for data processing and ETL (Extract, Transform, Load) workflows, with hands-on experience in using Databricks for building ETL pipelines and handling big data processing Experience with data warehousing platforms such as Amazon Redshift, or Snowflake. Strong knowledge of SQL and experience with relational (e.g., PostgreSQL, MySQL) databases. Familiarity with big data frameworks like Apache Hadoop, Spark, and Kafka for handling large datasets. Experienced with software engineering best-practices, including but not limited to version control (GitLab, Subversion, etc.), CI/CD (Jenkins, GITLab etc.), automated unit testing, and Dev Ops Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA) Good-to-Have Skills: Experience with cloud platforms such as AWS particularly in data services (e.g., EKS, EC2, S3, EMR, RDS, Redshift/Spectrum, Lambda, Glue, Athena) Strong understanding of data modeling, data warehousing, and data integration concepts Understanding of machine learning pipelines and frameworks for ML/AI models Professional Certifications (please mention if the certification is preferred or required for the role): AWS Certified Data Engineer (preferred) Databricks Certified (preferred) Soft Skills: Excellent critical-thinking and problem-solving skills Strong communication and collaboration skills Demonstrated awareness of how to function in a team setting Demonstrated presentation skills Equal opportunity statement Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status. We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation. What you can expect of us As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we’ll support your journey every step of the way. In addition to the base salary, Amgen offers competitive and comprehensive Total Rewards Plans that are aligned with local industry standards. Apply now for a career that defies imagination Objects in your future are closer than they appear. Join us. careers.amgen.com As an organization dedicated to improving the quality of life for people around the world, Amgen fosters an inclusive environment of diverse, ethical, committed and highly accomplished people who respect each other and live the Amgen values to continue advancing science to serve patients. Together, we compete in the fight against serious disease. Amgen is an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or any other basis protected by applicable law. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

Location Pune, Hyderabad, Gurgaon, Bangalore [Hybrid] : Python, PySpark, SQL, IAM, CloudFormation, StepFunctions, and Redshift. Not Ready to Apply Join our talent pool and we'll reach out when a job fits your skills.

Location Pune, Hyderabad, Gurgaon, Bangalore [Hybrid] : Python, Pyspark, SQL, AWS Services - AWS Glue, S3, IAM, Athena, AWS CloudFormation, AWS Code Pipeline, AWS Lambda, Transfer Family, AWS Lake Formation, and CloudWatch, CI/CD automation of AWS CloudFormation stacks Not Ready to Apply Join our talent pool and we'll reach out when a job fits your skills.