Job Description Data QA Engineer
n Location : Kolkata, India (Onsite/Hybrid)
n Experience : 2–4 years
n Employment Type: Full time
n ABOUT THE ROLE
nWe are hiring a Data QA Engineer for our data engineering team. This role is responsible for
nvalidating ETL pipelines and data platforms built on Azure Data Factory, Databricks, and
nMicrosoft Fabric, along with the downstream tables, reports, and models they feed. The core
nresponsibility is verifying data correctness, which is distinct from confirming that a pipeline
nexecuted without errors — the two are frequently conflated, and this role exists to keep them
nseparate.
n KEY RESPONSIBILITIES
n
- n
- Design and execute test plans covering source-to-target validation and transformation logicn
- for ETL pipelinesn
- Write SQL and PySpark scripts to verify accuracy, completeness, and consistency in Deltan
- Lake tablesn
- Perform regression testing on every pipeline change; a successful pipeline run does notn
- guarantee correct output, and validation must be independent of execution statusn




- Build and maintain reusable data quality checks (e.g., Great Expectations, dbt tests, orn
- custom PySpark frameworks) in place of one-off manual queriesn
- Reconcile data between source systems and target Lakehouse/Warehouse layers, andn
- investigate root cause when discrepancies are foundn
- Validate schema conformance, null/duplicate handling, referential integrity, and businessn
- rule adherence across Bronze/Silver/Gold layersn
- Validate Microsoft Fabric artifacts — Lakehouses, Warehouses, and semantic models —n
- including DirectLake mode behavior and cross-domain data consistencyn
- Apply consistent QA methodology across tools; the underlying platform (Databricks, Fabric,n
- or otherwise) should not change how rigorously data is validatedn
- Document test cases and defects with enough detail for engineers to act on them withoutn
- requiring additional clarificationn
- Work directly with the

📌 Data Quality Assurance Lead (Kolkata)
🏢 Finarb
📍 Kolkata