Inventory and document all existing Talend jobs, transformation logic, and reconciliation rules.
Operate the Datafold Migration Agent for automated bulk migration where supported.
Manually convert ETL jobs that cannot be automated and validate the correctness of each.
Pair-program with AI tooling to accelerate conversion — reviewing, fixing, and validating AI-generated output.
Build DBT models and Snowpark functions to replace legacy Talend jobs.
Implement automated data validation that surfaces quality and completeness issues via a Streamlit UI dashboard.
Build a diagnostic tool to test the health of the full software stack and data connectivity end-to-end.
Document all ETL logic changes throughout the migration.
Maintain up-to-date data lineage documentation for the full pipeline

4+ years of experience in data engineering with hands-on ETL development and migration.
Strong working knowledge of dbt and SQL-based transformation patterns.
Experience with Snowflake as a primary data platform.
Experience with Snowpark (Python or Java) for custom transformation logic.
Prior exposure to Talend or similar legacy ETL tools (SSIS, Informatica, etc.).
Familiarity with Datafold or similar data diff / migration validation tooling.
Experience building data quality monitoring or observability layers.
Comfort working with AI coding tools and reviewing/validating AI-generated code.

Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation.
Be part of a global team with equal opportunities for collaboration across continents and cultures.
Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards.

Data Engineer

Key skills