Sr Analyst, Data Integrity, Enablement & Validation

You will bring clarity to complex data landscapes—supporting the development and adoption of standardized metrics, validating data quality, reconciling inconsistencies, and embedding repeatable integrity checks that enhance confidence in analytics and enterprise reporting. This is an opportunity to combine technical expertise with business understanding and communication skills to translate complex data issues into clear findings, recommendations, and solutions; hence enabling the entire organization to make decisions based on trusted information.

What You’ll Do

• Partner with business, analytics, product, and technical stakeholders to define data requirements, metric definitions, business rules, and use cases.
• Validate internal and external data sources for accuracy, consistency, completeness, and usability with minimal supervision.
• Investigate and reconcile discrepancies across multiple datasets and reporting environments, identify root causes and recommend remediation.
• Develop, maintain, and enhance repeatable validation processes, reconciliation methodologies, and quality controls for critical business data.
• Validate new datasets, metrics, dashboards, and analytical products prior to broader adoption, and collaborate with data engineering and analytics teams to address upstream data quality issues.
• Monitor key datasets and metrics for anomalies, gaps, unexpected changes, and emerging data quality concerns, and develop reporting tools that provide visibility into data integrity.
• Support the development and governance of standardized enterprise metrics, definitions, and business rules, while maintaining clear documentation of data sources, lineage, methodologies, assumptions, and limitations.
• Enable analysts and business partners to effectively access, understand, and use trusted data for analysis and insights-generation.
• Translate complex technical findings into clear, non-technical language for business stakeholders and leadership to support informed decision-making.

What You Bring

• Bachelor’s degree in information technology, data analytics, computer science, finance, statistics, business, or related field.
• 5+ years of experience in data analytics, business intelligence, data quality, data governance, or related analytical discipline.
• Proficiency in SQL for investigating, identifying root causes of data discrepancies, validating, reconciling, and analyzing large and complex datasets across multiple systems.
• Strong understanding of relational databases, data warehousing, data pipelines, and enterprise reporting environments, with the ability to connect technical data structures to underlying business processes.
• Proven experience developing and applying data validation processes, quality assurance, business rules, and/or data governance practices in a business setting, to improve data accuracy and reliability.
• Familiarity with BI tools such as Power BI or Tableau.
• Strong analytical and problem-solving skills with exceptional attention to detail and the ability to clearly communicate complex data issues, methodologies, and findings to technical and non-technical audiences.
• Strong interpersonal, collaboration, organizational, documentation, and time-management skills, with the ability to work effectively and influence across teams without direct authority.
• Experience within healthcare, medical devices, or other complex data environments preferred.

What Sets You Apart

• Data Stewardship Mindset - You treat data as a business asset and drive integrity across systems and teams.
• Analytical Curiosity - You dig deep into data patterns and anomalies to uncover root causes.
• Clear Communicator - You make complex data stories understandable and actionable for any audience.
• Collaborative Approach - You build relationships across functions to align on definitions and outcomes.
• Systems Thinker - You connect upstream sources to downstream analytics and reporting impacts.
• Continuous Improver - You seek ways to enhance processes and ensure ongoing data reliability.