Sr. Manager, Technical Data Product Owner

McKessonAlpharetta, GA
22h

About The Position

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. Current Need: Ontada is advancing the future of oncology data and real‑world evidence — and we’re looking for a Senior Technical Data Product Owner to help shape how clinical data fuels our research products. In this role, you will lead a team of product owners and oversee end‑to‑end clinical data management workflows across Ontada’s core Data Platform. You will be responsible for transforming complex business needs into scalable data solutions—from requirements gathering to ingestion, integration, reconciliation, validation, and final delivery of research‑grade datasets. This position calls for a leader with strong technical acumen, exceptional cross‑functional collaboration skills, and a passion for building high‑quality, reliable data products. If you thrive in structured, fast‑moving environments and enjoy orchestrating complex workflows, this is an opportunity to have a meaningful impact on cancer research and evidence generation.

Requirements

  • Degree or equivalent experience. Typically requires 9+ years of professional experience and 1+ years of supervisory and/or management experience.
  • 9+ years in data management, data product management, or technical product management—preferably in healthcare, life sciences, or health tech.
  • Proven experience leading product owners or managing multiple complex workstreams.
  • Expertise with JIRA, Confluence, and Agile practices; strong capability in writing/refining user stories and acceptance criteria.
  • Strong experience translating business needs into data management requirements and actionable technical tasks.
  • Familiarity with data ingestion, ETL, integration, and reconciliation of multi‑modal healthcare datasets.
  • Demonstrated success collaborating across engineering, data science, and business stakeholders in highly matrixed environments.
  • Strong communication skills, with the ability to influence and partner at all levels.
  • Strategic thinker with the ability to drive near‑term delivery while shaping long‑term platform evolution.
  • Operates with strong ownership, accountability, and a mindset of automation, simplification, and continuous improvement.

Nice To Haves

  • Deep understanding of healthcare data standards (ICD‑10, SNOMED CT, LOINC, RxNorm) and data models (FHIR, OMOP, mCODE) highly preferred.
  • Up to 10% travel nationwide.

Responsibilities

  • Leadership & Team Management Lead and mentor product owners across four pods; foster a culture of ownership, operational excellence, and accountability. Ensure consistent, standardized data management practices and execution approaches across all pod teams.
  • Data Management & Execution Drive end‑to‑end clinical data management workflows that power Ontada’s research data products. Translate business requirements into clear data and technical specifications that align with Ontada’s data strategy. Align the data management roadmap with organizational priorities; define pod-level plans, milestones, dependencies, and required resources.
  • Operational Excellence Proactively identify risks, blockers, and cross‑team dependencies; develop and execute mitigation strategies. Own data management prioritization across pods, balancing speed, completeness, accuracy, and data quality. Partner with PMO and pod product owners to maintain accurate JIRA backlogs, including epics, user stories, and acceptance criteria. Build and maintain operational dashboards to provide visibility into progress, forecasting, resource allocation, risks, and timelines.
  • Quality Assurance & Continuous Improvement Ensure rigorous QA and validation processes to deliver research‑grade, high-integrity data. Continuously refine and improve data processes using quality metrics, operational insights, and customer feedback. Define and monitor pod-level KPIs that measure throughput, delivery performance, data quality, and operational stability.
  • Cross‑Functional Collaboration Work closely with engineering teams to ensure data workflows and technical processes are scalable, reusable, and efficient. Apply deep understanding of data models, data processing pipelines, and clinical data workflows to guide decision‑making.
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