Data Integration Specialist

1 day ago

Mount Abu, Rajasthan, India beBeeETL Full time ₹ 15,00,000 - ₹ 20,10,000

Our company is seeking a skilled Data Integration Specialist to join our team of talented data engineers.

The ideal candidate will have experience in designing and implementing efficient data pipelines using IBM DataStage (on Cloud Pak for Data), AWS Glue, and Snowflake. We are looking for someone who can work collaboratively with architects, business analysts, and data modelers to deliver critical data assets that support analytics and AI/ML use cases.

  • We require the successful candidate to 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.
  • Building and optimizing data flows for loading curated datasets into Snowflake, leveraging best practices for schema design, partitioning, and transformation logic is also required.
  • Participating in code reviews, performance tuning, and defect triage sessions will be necessary.
  • The chosen candidate must work closely with data governance teams to ensure lineage, privacy tagging, and quality controls are embedded within pipelines.
  • Contributing to CI/CD integration of ETL components using Git, Jenkins, and parameterized job configurations will be a requirement.
  • Troubleshooting and resolving issues in QA/UAT/Production environments as needed will be part of the job.
  • Adhering to agile delivery practices, sprint planning, and documentation requirements will also be necessary.

The successful candidate will have:

  • At least 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.

Prior experience with Collibra, BigID, or other metadata/governance tools; exposure to Data Mesh/Data Domain models; and experience with agile/Scrum delivery and Jira/Confluence tools are all considered advantageous.

AWS or Snowflake certification is a plus but not required.

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