Transformative Data Integration Expert

4 days ago

Mangalore, Karnataka, India beBeeDataIntegration Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Job Description

We are seeking a seasoned Data Integration Specialist to join our data engineering team.

The successful candidate will be responsible for designing, developing, and maintaining efficient data pipelines using cutting-edge technologies like IBM DataStage, AWS Glue, and Snowflake.

This role requires collaboration with architects, business analysts, and data modelers to ensure timely and accurate delivery of critical data assets supporting analytics and AI/ML use cases.

Key Responsibilities
  • Design and develop 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.
  • Adhere to agile delivery practices, sprint planning, and documentation requirements.
Required Skills and Qualifications

Our ideal candidate will have:

  • 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.

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