Data Engineer
4 days ago
We are seeking a skilled ETL Professional to join our data engineering team. The selected candidate will be responsible for designing, developing, and maintaining scalable and efficient data pipelines using IBM DataStage, AWS Glue, and Snowflake.
The role requires the ability to work with varied data sources, including flat files, APIs, Oracle, DB2, etc. The successful candidate will also be responsible for building and optimizing data flows for loading curated datasets into Snowflake, leveraging best practices for schema design, partitioning, and transformation logic.
Key Responsibilities:- Data Pipeline Development: Design, develop, and maintain ETL pipelines using IBM DataStage and AWS Glue/Lambda.
- Data Flow Optimization: Build and optimize data flows for loading curated datasets into Snowflake.
- Collaboration and Troubleshooting: Participate in code reviews, performance tuning, and defect triage sessions. Troubleshoot and resolve issues in QA/UAT/Production environments as needed.
- ETL Experience: 4+ years of experience in ETL development with at least 1–2 years in IBM DataStage (preferably CP4D version).
- AWS Experience: Hands-on experience with AWS Glue (PySpark or Spark) and AWS Lambda for event-based processing.
- Snowflake Experience: Experience working with Snowflake: loading strategies, stream-task, zero-copy cloning, and performance tuning.
- SQL and Scripting: Proficiency in SQL, Unix scripting, and basic Python for data handling or automation.
- Data Storage and Version Control: Familiarity with S3, version control systems (Git), and job orchestration tools.
- Data Profiling and Quality Validation: Experience with data profiling, cleansing, and quality validation routines.
- Understanding of Data Architecture and DevOps: Understanding of data lake/data warehouse architectures and DevOps practices.
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