Data Engineer

We are seeking a hands-on Data Engineer to own the data side of customer go-lives. You will validate and sign off on data migrations, develop high-quality SQL models that power BI dashboards, and implement automated data quality checks. Your work ensures data accuracy, trust, and performance across our analytics and migration platforms.

Key Responsibilities

Migration Validation:

• Design and execute end-to-end migration tests: row/aggregate parity, schema diffs, referential integrity, nullability, duplicates, and sampling.
• Produce migration sign-off packs documenting functional and performance validation.

SQL Development & Optimization:

• Build and optimize analytical SQL models (CTEs, window functions, incremental loads).
• Perform query performance tuning (EXPLAIN plans, indexing, statistics) with PostgreSQL.

Data Quality Automation:

• Implement and automate data quality checks using Great Expectations, Deequ/PyDeequ, or similar frameworks.
• Integrate validation into CI/CD pipelines with visible reporting.

Modeling & Documentation:

• Maintain well-documented SQL and dbt models with tests and exposures for traceability.
• Ensure all BI-facing datasets are reliable, performant, and documented.

Orchestration & Reliability:

• Productionize pipelines and checks in Apache Airflow with clear SLAs, monitoring, and alerting.
• (If applicable) Develop incremental pipelines to Snowflake or optimize batch loads in PostgreSQL.

Minimum Qualifications

• 4 to 7+ years of experience as a Data/Analytics Engineer.
• Advanced SQL expertise with strong RDBMS fundamentals (PostgreSQL required).
• Proven track record in data migration testing (parity, integrity, performance).
• Hands-on experience with at least one of:

                    dbt

                    Great Expectations / Deequ

                    Airflow

• Strong understanding of Git-based workflows and CI/CD pipelines.

Nice to Have

• Experience with Snowflake (Streams, Tasks, warehouse cost optimization).
• Exposure to BI stacks (Looker, Power BI, Tableau, Metabase) and metrics layers.
• Python for lightweight ETL, validation, and automation scripts.