Description

You will lead data quality assurance and metric validation for enterprise data assets.

This role is hybrid.

Responsibilities

• Validate metric definitions against source-of-truth tables and document root causes for discrepancies.
• Build and maintain repeatable checks, including sampling and reconciliation, within a central repository.
• Partner with BI developers, data engineers, and product analysts to triage defects and track remediation.
• Monitor data refreshes and lineage in Power BI, diagnosing DAX and modeling issues affecting accuracy.
• Produce clear issue summaries for stakeholders detailing what broke, where, why, and how it was fixed.

Required Skills

• 5+ years of experience working with large-scale enterprise data.
• Expert SQL proficiency with Oracle, including joins, window functions, and performance-aware queries.
• Hands-on experience with MongoDB, specifically aggregation pipelines and indexing.
• Demonstrated ability in Power BI validation, including data model checks and DAX basics.
• Familiarity with QA fundamentals, covering test case design and defect lifecycles.
• Working knowledge of the SDLC in agile environments, using Jira.
• Experience with BI semantic modeling (Star/Snowflake) and data governance concepts.
• Proficiency in MS Excel and exposure to CI/CD tools like Jenkins or Ansible Tower.

Preferred Skills

• Strong communication skills for concise issue writeups and stakeholder alignment.

Key Skills

Education

Bachelor's degree