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Specialized data-quality role with broad tech stack and mid-level seniority, moderate applicant density.
Skills are moderately transferable across industries but require enterprise data governance experience.
Many mandatory hands-on platform and framework requirements create stringent shortlisting filters.
Lead design, implementation, and continuous improvement of the Enterprise Data Quality Framework across the data ecosystem including ingestion pipelines, data warehouses, and Data Products.
Establish and operationalize automated data quality capabilities such as profiling, validation, monitoring, issue management, and KPI scorecards to improve enterprise data accuracy, completeness, and reliability.
Partner with Data Engineering, Enterprise Data Management, Product teams, and business stakeholders to embed Data-as-a-Product quality practices and governance throughout the data lifecycle.
Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, Information Systems or related field; Master's preferred.
Intermediate level of relevant work experience required.
Strong hands-on experience leading enterprise Data Quality programs and frameworks across large-scale Data Warehouse and Data Product environments.
Experience with modern cloud data platforms and tools like Snowflake, Databricks, SQL, Matillion, dbt, and Power BI.
Experienced in establishing data quality, governance, metadata management, lineage, and stewardship practices within enterprise data ecosystems.
Skilled in implementing automated data quality controls and observability solutions across end-to-end data pipelines and products.
Capable of partnering cross-functionally with technical and business teams to operationalize scalable data quality standards and certification processes.