Role Overview :

We are looking for a Fabric Data Quality Engineer. The role will focus on building automated data-quality frameworks, validating migrated data, performing source-to-target reconciliation, and ensuring data and BI outputs meet business requirements.

This is a hands-on engineering role requiring strong SQL, Python/PySpark, Microsoft Fabric/Azure, data validation, and reconciliation experience.

Key Responsibilities :

- Build and maintain automated data-quality and validation frameworks for Fabric pipelines.
- Develop checks for row counts, completeness, nulls, duplicates, referential integrity, aggregations, variance, data freshness, latency, schema drift, and data anomalies.
- Build automated source-to-target reconciliation between legacy and Fabric environments.
- Compare row counts, aggregates, column values, and sampled records to identify migration issues.
- Investigate data discrepancies and perform root-cause analysis across source, transformation, and target layers.
- Validate incremental loads, CDC, historical loads, and late-arriving data.
- Develop and maintain regression test suites for migrated data objects and transformations.
- Validate Power BI semantic models, measures, KPIs, relationships, and report outputs.
- Support QA, UAT, defect management, and release-readiness activities.
- Integrate data-quality checks into CI/CD pipelines where required.
- Monitor data quality across completeness, accuracy, consistency, conformity, uniqueness,



and timeliness.
- Work closely with Data Engineers, Architects, Analytics, QA, and business stakeholders.

Required Skills :

- 4+ years of experience in Data Engineering, Data Quality, Data Validation, ETL Testing, or related areas.
- Solid SQL, including joins, CTEs, window functions, aggregations, and reconciliation.
- Strong Python and PySpark experience.
- Hands-on experience with Microsoft Fabric, including Lakehouse, Warehouse, Notebooks, and Pipelines.
- Experience with Azure Data Factory, Azure Synapse, or Databricks is also relevant.
- Experience building automated data validation/testing frameworks.
- Strong experience with source-to-target reconciliation and data migration testing.
- Working knowledge of Power BI and semantic model validation.
- Experience with Git, Azure DevOps, CI/CD, and code reviews.
- Strong troubleshooting and root-cause analysis skills.
- Experience working with distributed/global teams and excellent communication skills.

Preferred Skills :

- Experience with legacy warehouse-to-Fabric/Azure/Databricks migrations.
- Microsoft Fabric certifications such as DP-700 or DP-600.
- Experience with Microsoft Purview Data Quality.
- Experience with Delta Lake, CDC, anomaly detection, or data observability tools.
- Experience working with large datasets and optimizing data validation workloads.
- Experience with Agile/Scrum delivery.

📌 Simform Solutions - Data Quality Engineer - Microsoft Fabric (India)
🏢 Simform
📍 India