Sr. Data Quality Analyst

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. CoverMyMeds is seeking a Senior Data Quality Analyst to build and mature a comprehensive data quality capability from the ground up. Working closely with Data Domain Officers, business stakeholders, data teams, and contractors, you'll translate business expectations into practical standards, processes, quality rules, dashboards, and services that can be implemented across our data platforms and business lines. This highly visible opportunity is ideal for a collaborative, creative self-starter who is comfortable navigating ambiguity and turning data quality needs into scalable solutions. Job Responsibilities: - Design and build the enterprise data quality framework - dimensions, scoring methodology, thresholds, and escalation paths - so that quality is measured consistently across domains rather than ad hoc per team - Stand up data observability capability (freshness, volume, schema drift, distribution, lineage-aware anomaly detection) across priority pipelines and datasets, so quality issues surface before they reach consumers - Define and operationalize data quality rules and checks for critical data elements, working with data owners and stewards to encode business meaning into testable logic - Build the data quality service layer: reusable rule libraries, monitoring dashboards, and alerting that downstream teams can plug into rather than rebuild - Conduct data quality assessments, triage root causes (source, pipeline, model, or definitional), and drive remediation plans with data owners and engineering teams through to closure - Evaluate, implement, and administer data quality and observability tooling (e.g., Collibra, Informatica, Monte Carlo, Great Expectations) as part of the broader data catalog and lineage stack - Establish data quality SLAs/SLOs with data owners and platform teams, and report quality and observability KPIs (completeness, accuracy, timeliness, incident MTTR) to track the health of the capability over time - Partner with legal, compliance, and privacy teams to ensure quality controls meet regulatory requirements (e.g., HIPAA, GDPR, CCPA) without duplicating existing governance processes. - Train data stewards and business users on the data quality framework, tooling, and how to interpret observability signals and escalate issues - Act as the subject matter expert on data quality and observability practices, advising stakeholders on how to design new systems and pipelines with quality built in rather than bolted on - Proactively identify systemic data quality risks (not just individual incidents) and escalate capability gaps to leadership Job Qualifications: Bachelor's degree in Information Technology, Computer Science, Business Administration, or a related field (Master's degree preferred) or related experience Typically requires 7+ years of experience in data quality, data observability, data engineering, or data governance, including direct experience building (not just documenting) a data quality capability within a large, complex organization Proven experience designing data quality frameworks and implementing data observability tooling and practices Strong understanding of data