Senior Analyst - Data Quality

Design, develop, and implement SQL and Databricks data quality validations to ensure completeness, consistency, and reliability across shared data platforms.

Build reusable Python automation components and monitoring frameworks for scalable data validation across multiple pipelines and products.

Create and maintain Power BI dashboards and reports to provide actionable data quality insights, lead root cause analysis for data anomalies, and partner with engineering teams for remediation.

Bachelor’s degree in Quantitative field (Engineering, Statistics, Applied Math, Computer Science, Data Science, Economics, or related).

5+ years of experience in data quality management, ETL systems, or data analytics roles.

Advanced SQL skills including CTEs, window functions, complex joins, and performance tuning; experience with Databricks, Apache Spark, or PySpark required.

Strong Python programming skills for scripting and automation; experience with cloud data platforms such as AWS, MS-Azure, Snowflake, or Amazon Redshift.

Proven ability to translate complex data pipelines into scalable quality validations and monitoring solutions within large or global organizations.

Experience collaborating cross-functionally to embed data quality by design and influence data product roadmaps.

Hands-on expertise managing and optimizing ETL pipelines alongside strong documentation and communication skills for stakeholder engagement.