Director, Technical & Platform Product Management

McKesson•Irving, TX

23h•Hybrid

About The Position

The Director, Technical & Platform Product Management leads strategy, development, launch, and adoption of data, analytics, and related technology platform capabilities for McKesson’s pharmacy technology business. The role partners across teams to understand data consumers’ needs, how they consume data, and which business capabilities the platform must support. It owns the data product backlog and translates consumer and business needs into executable product requirements and priorities in close partnership with engineering and other product teams. The position defines the data platform vision, value propositions, roadmap, and build-versus-buy decisions; leads discovery and validates needs and feasibility; and shapes reusable ingestion, pipeline, modeling, and data-access capabilities. It also guides data migration and consumer adoption, establishes measurable data expectations, monitors platform performance and usage, and collaborates on governance and lifecycle decisions. Success is measured by data freshness, completeness, quality, availability, adoption, delivery efficiency, and business value. The role may be performed in a hybrid arrangement under McKesson’s in-office/work-from-home model. Candidates located in the Dallas–Fort Worth area may be expected to work at the Las Colinas office at least two days per week; designated office days may depend on team needs and business priorities. Some travel may be required for cross-site collaboration and customer or partner engagements. Applicants must be authorized to work in the United States without current or future employer immigration support or sponsorship.

Requirements

Degree or equivalent and typically 10 or more years of relevant experience; fewer years may be required with relevant master’s or doctoral qualifications.
Bachelor’s degree in computer science, engineering, information systems, a related technical discipline, or equivalent relevant professional experience.
10 or more years of progressive product management experience supporting enterprise software, SaaS, platform, infrastructure, or developer-facing technology products.
Experience leading at least one technically complex platform or product from initial concept through production launch and adoption.
Experience defining product strategy, roadmaps, requirements, priorities, success measures, and adoption plans for technical data products such as a data lake, data warehouse, or enterprise data warehouse.
Experience working directly on data migration with software engineers and architects on distributed systems, APIs, integrations, data models, cloud architecture, scalability, reliability, security, or observability.
Hands-on experience with at least one of the following: reviewing API specifications, querying data using SQL or Python, evaluating logs or telemetry, or developing lightweight technical prototypes.
Experience defining and using measurable platform or service indicators, such as adoption, availability, latency, throughput, error rates, recovery objectives, delivery cycle time, infrastructure cost, or developer experience.
Experience managing platform interfaces through versioning, backward compatibility, migration planning, dependency management, or deprecation.
Applicants must be currently authorized to work in the United States on a full-time basis without the need for employer support or sponsorship now or in the future.

Nice To Haves

Experience with Databricks and/or Snowflake environments and application of their AI/ML features.
Previous experience in software engineering, systems architecture, technical leadership, data engineering, or infrastructure engineering.
Experience developing products for technical users, including APIs, SDKs, developer portals, self-service workflows, integration standards, documentation, or CI/CD tooling.
Experience with public cloud platforms, containerized applications, event streaming, infrastructure as code, observability platforms, identity services, or developer platforms.
Experience with AI or machine learning platforms, large language model orchestration, vector databases, responsible AI practices, or production data pipelines.
Experience launching pilot or beta programs with defined user groups, measurable success criteria, operational readiness requirements, and data-informed launch decisions.
Experience with marketplace or multi-sided platform products.
Advanced degree in computer science, engineering, data science, business, or a related discipline.

Responsibilities

Define the data platform strategy and roadmap, including capability vision, target consumers, value propositions, priorities, and build-versus-buy decisions for McKesson Pharmacy System’s Platform.
Lead data product discovery with data teams to identify required data, consumption methods, and supported business capabilities; validate needs and feasibility with engineering and architecture before investment.
Define requirements for reusable data ingestion and pipelines, including batch, streaming, and change data capture, as well as transactional and analytical data modeling.
Make data available through APIs, events, extracts, and data products.
Own the data product backlog and translate consumer needs into capabilities, epics, stories, acceptance criteria, and roadmap priorities that engineering can execute.
Define data-related platform deliverables while balancing business value, dependencies, risk, security, technical debt, and cost.
Define legacy-platform data migration requirements, including transformation, mapping, enrichment, and reconciliation; develop onboarding, documentation, and feedback strategies for data consumers.
Establish measurable expectations for data freshness, completeness, quality, and availability; monitor adoption, pipeline reliability, latency, cost, and consumer experience, using telemetry and feedback to guide roadmap decisions.
Partner with engineering, architecture, security, and data teams on data quality, governance, lineage, cataloging, stewardship, PHI/PII, retention, security, access controls, versioning, migration, and deprecation.
Communicate data-platform trade-offs to engineering, product, customers, and executive audiences, and align cross-functional decisions without prescribing engineering implementation.
Lead the strategy, development, launch, and adoption of platform capabilities across data, analytics, and related technology platforms.