Lead Data Engineer
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Role details
Tech stack
Requirements
- Analytics Engineering / Data Modelling: Strong hands-on experience with dbt (data build tool), data modelling, transformation layers, testing, and documentation.
- Backend & Integration: Backend development, APIs, Kafka, and experience working with Cycle Manager business logic/workflows.
- Frontend Validation: Exposure to workflow/UI validation using React/TypeScript or Angular.
- QA & Migration Validation: Experience with QA validation, data reconciliation, parallel-run testing, defect resolution, and final sign-off.
The ideal candidate should have broad, hands-on experience across these areas rather than being focused only on Snowflake/data engineering. We are looking for someone who can take end-to-end ownership of the migration, from understanding existing business logic and pipelines through development, validation, parallel runs, and production cutover.
Candidates with strong Snowflake + dbt (data build tool)+ migration experience and verify the additional backend, Kafka, frontend validation, and QA/parallel-run exposure before submission. Recent Snowflake/dbt migration roles similarly emphasize hands-on pipeline migration, modelling, reconciliation, validation, and cutover ownership.
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