Manager, PDS Data Domain

At Bristol Myers Squibb, our employees often ask, “Who are you working for?”—a question that fuels collaboration, accountability, and urgency in our work. Our purpose-driven culture inspires us to discover, develop, and deliver innovative medicines to prevail over serious diseases. We offer uniquely interesting and meaningful work, opportunities for growth, and a supportive environment that values inclusion, wellbeing, flexibility, and comprehensive benefits. This is work that transforms the lives of patients, and the careers of those who do it.

Position Summary Bristol Myers Squibb is seeking a manager to advance data governance and data quality within PDS, helping business functions manage and use data as a trusted, reusable business asset. The role engages business and functional stakeholders, process owners, data owners and stewards to understand business needs and build alignment on governance initiatives, data standards, ownership, quality expectations and measurable outcomes. Working with data engineering and technology teams, the Manager translates agreed priorities into actionable requirements, coordinates data-quality issue resolution and supports the delivery and adoption of governed data products and analytics using Databricks and enterprise data lakes. The Manager communicates the business value of well-governed, high-quality data and helps users apply reliable insights in operational decisions. The Manager owns assigned workstreams and deliverables, with strategic direction and prioritization provided by the Senior Manager or Data Domain Lead. Key Responsibilities – Data Quality and Governance · Work with data owners and stewards to document critical data elements, definitions, ownership, data-quality rules and acceptance thresholds. · Support metadata, lineage, access, privacy and data-quality controls required for governed and fit-for-purpose data products. · Investigate data issues with business and technical teams; document root cause, resolution and prevention actions. · Promote consistent governance practices across data lake, Databricks and downstream data-product delivery. Business Analysis and Adoption · Analyze operational pain points and translate them into prioritized data-product backlog items. · Prepare demonstrations, user guidance, training materials and adoption communications. · Collect user feedback and product measures to support continuous improvement. · Help users discover available data, understand product definitions and apply data consistently in business decisions. Data Platform and Product Execution Support end-to-end delivery of data products and analytics for an assigned PDS domain or use case, from discovery and requirements through testing, release and adoption. Work with data engineering teams to use enterprise data lake and Databricks capabilities for data ingestion, transformation, curation and consumption. Gather and document business requirements, data definitions, user stories, acceptance criteria, source-to-target needs and process impacts. Help define reusable data products with clear consumers, business value, ownership, service expectations and measurable success criteria. Coordinate working sessions with business experts, data stewards, data engineers and technology teams. Track actions, risks, dependencies, decisions and delivery milestones; escalate issues promptly. Collaboration and Ways of Working · Engage business and functional stakeholders, process owners, data owners and stewards to understand business needs, communicate the value of data governance and data quality, and build alignment on priorities, ownership and expected outcomes. · Facilitate cross-functional discussions to agree on data standards, data-quality expectations and remediation priorities; coordinate with business and technology teams to implement agreed actions and drive adoption of data governance initiatives. · Contribute to a practical, inclusive and data-driven culture within PDS. Qualifications & Experience Required · Bachelor's or master's degree in engineering, life sciences, data science, information systems or a related field. · 5 to 7 years of relevant experience across data governance, data quality, data analytics or digital delivery, partnering with business functions such as operations, manufacturing, supply chain or quality to establish and use trusted data as a business asset; regulated-industry experience is preferred. · 2+ years of practical experience delivering data or analytics solutions using Databricks and enterprise data lakes, applying governance standards and data-quality controls. Ability to engage business stakeholders, translate their needs into actionable requirements and clearly explain how well-governed, high-quality data enables reliable insights, reuse and business value. · Experience with SAP master data, including business-partner, material, vendor, customer or other relevant master-data domains. · Experience with data-quality profiling, rule definition, monitoring, issue management and root-cause analysis. · Experience with data-governance practices such as stewardship, ownership, metadata, lineage, access controls and critical-data-element management. · Knowledge of operational systems such as SAP, Veeva, laboratory information management systems or supply-chain planning platforms. · Familiarity with good practice requirements and regulated data controls for applicable domains. · Practical experience working with enterprise data lakes, including data ingestion, transformation, curation and consumption patterns. · Hands-on or delivery experience with Databricks, including SQL, notebooks, workflows or jobs; familiarity with governed catalogs and layered data architecture is expected. · Experience defining or delivering data products, including requirements, ownership, quality expectations, user acceptance and adoption measures. · Experience documenting requirements, coordinating cross-functional work and supporting testing, training or adoption. · Ability to translate business questions into clear data needs, user stories and acceptance criteria. · Working knowledge of SQL and modern data-platform concepts; exposure to Python, visualization or data-quality tools is helpful. · Clear communication, organization, collaboration and problem-solving skills. What Sets This Role Apart · Platform-to-value impact : Connects enterprise data lake and Databricks capabilities to practical PDS outcomes. · Data governance and quality mindset: Transforms data into a valuable asset by identifying gaps and improving ways of working through a data-quality-focused approach. · Trusted data foundation : Connects data governance through clear ownership and standards with data quality through measurable controls and issue resolution, enabling reliable business decisions. · Data-product mindset : Builds reusable, governed data assets around clear users, value and adoption. · End-to-end exposure : Contributes from discovery and data-quality definition through testing, launch and adoption. · Collaborative role : Connects business, governance and technology teams around shared outcomes. · Growth pathway : Builds the experience needed to lead larger data domains and product portfolios over time. Our Culture and Applicant Information At BMS, every employee contributes to our vision of transforming patients' lives through science. Our values of passion, innovation, urgency, accountability, inclusion and integrity help colleagues bring their best to work. If this role interests you but your experience does not perfectly match every qualification, we encourage you to apply.

We hire for skills and capabilities, not just credentials – if this role excites you, but doesn’t perfectly match your resume, we encourage you to apply anyway.

How We Work Where you work matters – because collaboration, innovation and patient impact happen in many settings. Our roles are structured across four work models: site-essential, site-by-design, field-based and remote-by-design. The model assigned to this role is based on its core responsibilities. Learn more at https://careers.bms.com/ways-of-working.

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R1607170 : Manager, PDS Data Domain