Sr. Manager, Technical Data Product Owner

Current Need:

Ontada is advancing the future of oncology data and realworld 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 endtoend 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 researchgrade datasets. This position calls for a leader with strong technical acumen, exceptional crossfunctional collaboration skills, and a passion for building highquality, reliable data products.

If you thrive in structured, fastmoving environments and enjoy orchestrating complex workflows, this is an opportunity to have a meaningful impact on cancer research and evidence generation.

Key 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 endtoend 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 crossteam 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 researchgrade, highintegrity 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.

CrossFunctional 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 decisionmaking.

Minimum Experience:

• Degree or equivalent experience. Typically requires 9+ years of professional experience and 1+ years of supervisory and/or management experience.

Critical Skills:

• 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 multimodal 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 nearterm delivery while shaping longterm platform evolution.

• Operates with strong ownership, accountability, and a mindset of automation, simplification, and continuous improvement.

• Deep understanding of healthcare data standards (ICD10, SNOMED CT, LOINC, RxNorm) and data models (FHIR, OMOP, mCODE) highly preferred.

• Up to 10% travel nationwide.