Senior ETL Specialist

7 days ago

Mangalore, Karnataka, India beBeeETLDeveloper Full time ₹ 20,00,000 - ₹ 25,00,000
ETL Developer

A seasoned ETL developer with expertise in designing, developing, and maintaining data pipelines using IBM DataStage (on Cloud Pak for Data), AWS Glue, and Snowflake is sought after to join our team.

The ideal candidate will have hands-on experience with IBM DataStage (preferably CP4D version), AWS Glue (PySpark or Spark), and AWS Lambda for event-based processing. Experience working with Snowflake: loading strategies, stream-task, zero-copy cloning, and performance tuning is also highly desirable.

Additional requirements include proficiency in SQL, Unix scripting, and basic Python for data handling or automation, as well as familiarity with S3, version control systems (Git), and job orchestration tools. Experience with data profiling, cleansing, and quality validation routines, as well as understanding of data lake/data warehouse architectures and DevOps practices is a must.

  • 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.
  • Build and optimize data flows for loading curated datasets into Snowflake, leveraging best practices for schema design, partitioning, and transformation logic.
  • Participate in code reviews, performance tuning, and defect triage sessions.
  • Work closely with data governance teams to ensure lineage, privacy tagging, and quality controls are embedded within pipelines.
  • Contribute to CI/CD integration of ETL components using Git, Jenkins, and parameterized job configurations.
  • Troubleshoot and resolve issues in QA/UAT/Production environments as needed.
Requirements:
  • 4+ years of experience in ETL development with at least 1–2 years in IBM DataStage (preferably CP4D version).
  • Hands-on experience with AWS Glue (PySpark or Spark) and AWS Lambda for event-based processing.
  • Experience working with Snowflake: loading strategies, stream-task, zero-copy cloning, and performance tuning.
  • Proficiency in SQL, Unix scripting, and basic Python for data handling or automation.
  • Familiarity with S3, version control systems (Git), and job orchestration tools.
  • Experience with data profiling, cleansing, and quality validation routines.
  • Understanding of data lake/data warehouse architectures and DevOps practices.
Nice to Have:
  • Experience with Collibra, BigID, or other metadata/governance tools.
  • Exposure to Data Mesh/Data Domain models.
  • Experience with agile/Scrum delivery and Jira/Confluence tools.
  • AWS or Snowflake certification is a plus.

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