ETL Developer - Datastage

<p><p><b>Job Title : </b> ETL Developer DataStage, AWS, Snowflake.<br/><br/><b>Experience : </b> 5- 7 Years.<br/><br/><b>Location : </b> Remote.<br/><br/><b>Job Type : </b> Full-time.</p><p><br/></p><p><b>About the Role :</b></p><p><b><br/></b></p><p>We are looking for a talented and motivated ETL Developer / Senior Developer to join our data engineering team.</p><p><br/></p><p>You will work on building scalable and efficient data pipelines using IBM DataStage (on Cloud Pak for Data), AWS Glue, and Snowflake.</p><p><br/></p><p>You will collaborate with architects, business analysts, and data modelers to ensure timely and accurate delivery of critical data assets supporting analytics and AI/ML use cases.</p><p><b><br/></b></p><p><b>Key Responsibilities :</b></p><p><br/></p><p>- Design, develop, and maintain ETL pipelines using IBM DataStage (CP4D) and AWS Glue/Lambda for ingestion from varied sources like flat files, APIs, Oracle, DB2, etc.</p><p><br/></p><p>- Build and optimize data flows for loading curated datasets into Snowflake, leveraging best practices for schema design, partitioning, and transformation logic.<br/><br/></p><p>- Participate in code reviews, performance tuning, and defect triage sessions.<br/><br/></p><p>- Work closely with data governance teams to ensure lineage, privacy tagging, and quality controls are embedded within pipelines.<br/><br/></p><p>- Contribute to CI/CD integration of ETL components using Git, Jenkins, and parameterized job configurations.<br/><br/></p><p>- Troubleshoot and resolve issues in QA/UAT/Production environments as needed.<br/><br/></p><p>- Adhere to agile delivery practices, sprint planning, and documentation Skills and Experience :</b></p><p><br/></p><p>- 4+ years of experience in ETL development with at least 1- 2 years in IBM DataStage </p><p>(preferably CP4D version).</p><p><br/></p><p>- Hands-on experience with AWS Glue (PySpark or Spark) and AWS Lambda for event-based </p><p>processing.<br/><br/></p><p>- Experience working with Snowflake : loading strategies, stream-task, zero-copy cloning, and performance tuning.<br/><br/></p><p>- Proficiency in SQL, Unix scripting, and basic Python for data handling or automation.<br/><br/></p><p>- Familiarity with S3, version control systems (Git), and job orchestration tools.<br/><br/></p><p>- Experience with data profiling, cleansing, and quality validation routines.<br/><br/></p><p>- Understanding of data lake/data warehouse architectures and DevOps to Have :</b></p><p><br/></p><p>- Experience with Collibra, BigID, or other metadata/governance tools.</p><p><br/></p><p>- Exposure to Data Mesh/Data Domain models.<br/><br/></p><p>- Experience with agile/Scrum delivery and Jira/Confluence tools.<br/><br/></p><p>- AWS or Snowflake certification is a plus.</p><br/></p> (ref:hirist.tech)