Data Quality Analyst - Senior 2

Lead design, implementation, and evolution of Enterprise Data Quality Framework across data ecosystem including pipelines, warehouses, semantic layers, and Data Products.

Establish and manage automated data quality capabilities such as profiling, validation, monitoring, issue management, and KPIs to improve data accuracy, completeness, consistency, timeliness, and reliability.

Partner with Data Engineering, Product Management, and business teams to embed data quality practices across the data lifecycle including governance, certification, root cause analysis, and proactive remediation.

Bachelor's degree in Computer Science, Information Technology, Data Analytics, Engineering, Information Systems, or related field (Master's preferred).

Intermediate level relevant work experience required (senior level implied).

Strong hands-on experience with enterprise Data Quality programs and frameworks including profiling, validation, reconciliation, monitoring, and issue management across large data environments.

Expertise in Data Quality, Data Governance, Metadata Management, Data Lineage, Stewardship, and Data-as-a-Product practices with ability to implement scalable automated quality controls and KPIs using modern cloud platforms such as Snowflake, Databricks, SQL, Matillion, dbt, Power BI.

Experienced in leading enterprise-scale data quality initiatives within large, modern data ecosystems involving Data Warehouses, Lakehouses, and Data Products.

Technical and strategic proficiency integrating data quality with governance, metadata management, certification, and data stewardship across complex data lifecycles.

Comfortable collaborating cross-functionally to operationalize data quality controls embedded in data pipelines supporting Analytics, ML, and GenAI use cases.