Job Title: Lead / Manager - Data QA Engineering (Databricks Lakehouse)
Location: Addison TX (Onsite)
Job Type: Contract
Responsibilities:
- Lead mentor and manage a team of Data QA Engineers supporting multiple data domains and initiatives.
- Define and evolve enterprise data QA strategy standards and best practices aligned to Lakehouse architecture and data governance.
- Establish QA engagement models across DEV QA and UAT phases to ensure early and continuous quality validation.
- Own data quality KPIs dashboards and continuous improvement initiatives.
- Oversee design and execution of data quality testing across Delta Lake tables pipelines and analytical views.
- Ensure validation of schema enforcement schema evolution constraints and incremental/CDC processing.
- Drive adoption of automated data quality checks embedded within Databricks workflows and orchestration.
- Review and approve SQL-based validation logic reconciliation frameworks and regression test coverage
- Enterprise data QA strategy standards and operating model
- Automated data quality frameworks and reusable validation assets
- Data quality metrics dashboards and executive reporting
- QA/UAT sign-off and production readiness documentation
Skills:
- BA or BS in a STEM field preferred advanced degree a plus.
- 8 12 years in data quality engineering analytics QA or data engineering roles with 3 5 years in a lead or managerial capacity.
- Strong hands-on SQL expertise and experience designing scalable data validation frameworks.
- Proven experience leading QA for Azure Databricks / Lakehouse platforms (Delta Lake SQL endpoints Unity Catalog preferred).
- Deep understanding of canonical/domain modeling and dimensional (Kimball/star schema) concepts.
- Experience validating S2T mappings data lineage and complex transformation logic.
- Familiarity with DAMA-DMBOK data governance and data quality management practices will be a plus.
- Experience in insurance or financial services data (ACORD familiarity a strong plus).
Job Title: Lead / Manager - Data QA Engineering (Databricks Lakehouse) Location: Addison TX (Onsite) Job Type: Contract Responsibilities: Lead mentor and manage a team of Data QA Engineers supporting multiple data domains and initiatives. Define and evolve enterprise data QA strategy standards a...
Job Title: Lead / Manager - Data QA Engineering (Databricks Lakehouse)
Location: Addison TX (Onsite)
Job Type: Contract
Responsibilities:
- Lead mentor and manage a team of Data QA Engineers supporting multiple data domains and initiatives.
- Define and evolve enterprise data QA strategy standards and best practices aligned to Lakehouse architecture and data governance.
- Establish QA engagement models across DEV QA and UAT phases to ensure early and continuous quality validation.
- Own data quality KPIs dashboards and continuous improvement initiatives.
- Oversee design and execution of data quality testing across Delta Lake tables pipelines and analytical views.
- Ensure validation of schema enforcement schema evolution constraints and incremental/CDC processing.
- Drive adoption of automated data quality checks embedded within Databricks workflows and orchestration.
- Review and approve SQL-based validation logic reconciliation frameworks and regression test coverage
- Enterprise data QA strategy standards and operating model
- Automated data quality frameworks and reusable validation assets
- Data quality metrics dashboards and executive reporting
- QA/UAT sign-off and production readiness documentation
Skills:
- BA or BS in a STEM field preferred advanced degree a plus.
- 8 12 years in data quality engineering analytics QA or data engineering roles with 3 5 years in a lead or managerial capacity.
- Strong hands-on SQL expertise and experience designing scalable data validation frameworks.
- Proven experience leading QA for Azure Databricks / Lakehouse platforms (Delta Lake SQL endpoints Unity Catalog preferred).
- Deep understanding of canonical/domain modeling and dimensional (Kimball/star schema) concepts.
- Experience validating S2T mappings data lineage and complex transformation logic.
- Familiarity with DAMA-DMBOK data governance and data quality management practices will be a plus.
- Experience in insurance or financial services data (ACORD familiarity a strong plus).
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