Job Summary
Job Description:-
- Demonstrate years of data engineering experience with a proven track record of migrating from legacy ETL/iPaaS tools (SnapLogic, Datastage) to a modern ELT stack using Fivetran tool
- Design the target ELT state using Fivetran for automated data ingestion and staging.
- Strong understanding of FiveTran Architecture and hands on experience in different source connectors
- Implement data validation and testing frameworks to ensure zero data loss or discrepancies during the legacy pipeline cutover
- Build custom Fivetran extensions using Python, REST APIs, and Cloud Functions for unsupported legacy applications.
- Audit legacy ETL/iPaaS configurations to map out existing data sources, targets, and complex transformation logic for migration
- Design strict data validation protocols to run parallel testing and ensure 100% data parity between the legacy systems and the new Fivetran environment.
- Manage the historical data backfill process, troubleshooting API rate limits, large volume sync errors, and network bottleneck issues.
Key Responsibilities
Job Description:-
- Demonstrate years of data engineering experience with a proven track record of migrating from legacy ETL/iPaaS tools (SnapLogic, Datastage) to a modern ELT stack using Fivetran tool
- Design the target ELT state using Fivetran for automated data ingestion and staging.
- Strong understanding of FiveTran Architecture and hands on experience in different source connectors
- Implement data validation and testing frameworks to ensure zero data loss or discrepancies during the legacy pipeline cutover
- Build custom Fivetran extensions using Python, REST APIs, and Cloud Functions for unsupported legacy applications.
- Audit legacy ETL/iPaaS configurations to map out existing data sources, targets, and complex transformation logic for migration
- Design strict data validation protocols to run parallel testing and ensure 100% data parity between the legacy systems and the new Fivetran environment.
- Manage the historical data backfill process, troubleshooting API rate limits, large volume sync errors, and network bottleneck issues.