Dir , Commercial Data Capability

MSD•Rahway, NJ

6d•Hybrid

About The Position

We are seeking a bold, forward-thinking, and technically grounded leader to join our company Digital Human Health (DHH) organization and play a pivotal role in shaping the future of our commercial data capabilities. This role is the "Head of Platform & Engineering Excellence." This leader and their team provide the foundational platforms, tools, and services (quality, ops, GenAI infra) that Core data domains/solutions and the Emerging business solutions teams will consume. This leader serves as the primary engineering and platform partner to Core Data Domains and Emerging Business Solutions teams, providing the foundational capabilities they need to build and scale their respective data products. This leader will lead four specialized teams — Data Quality & Business Rules Management, Innovation Capabilities, Data Operations, and Foundational Capabilities — with a mandate to modernize our data infrastructure, embed Generative AI solutions across the commercial data organization, and ensure the long-term resilience and sustainability of our data platforms. Additionally, This leader will serve as the organization's champion for Data Architecture & Engineering excellence and embed AI assisted data product development as the standard for how we operate. This leader will lead the team that builds the foundational GenAI infrastructure (the "factory"), while the Core and Emerging business solutions teams use that factory to build specific GenAI-powered data products.

Requirements

B.S. or M.S. in Engineering or related field (Business, Analytics, Engineering, Pharmacy, Technology fields, Liberal arts, Computer Science, Engineering, Data Science, etc.)
Minimum 10+ years of relevant work experience with a demonstrated track record in data architecture, data platform engineering, or data product leadership, with meaningful experience working in the biopharma or healthcare industry
AI Architecture
Business Intelligence (BI)
Data Architecture Development
Database Administration
Data Engineering
Data Infrastructure
Data Lineage
Data Management
Data Modeling
DataOps
Data Quality
Data Quality Test Automation
Data Visualization
Design Applications
Generative AI
Information Management
Microsoft Azure Batch Artificial Intelligence (AI)
Product Management Leadership
Responsible AI
Software Development
Software Development Life Cycle (SDLC)
Strategic Thinking
System Designs

Nice To Haves

Hands-on experience with specific GenAI and ML platform tooling such as Azure OpenAI Service, AWS Bedrock, Google Vertex AI, LangChain, LlamaIndex, or equivalent LLM orchestration frameworks
Experience implementing AI governance and responsible AI frameworks, including model transparency, bias assessment, data lineage for AI pipelines, and audit-readiness for AI-generated outputs in regulated industries
Familiarity with commercial biopharma data ecosystems and the specific challenges of preparing pharma commercial data (HCP data, promotional content, patient-linked data) for GenAI consumption
Experience building or managing vector store implementations and embedding pipelines (e.g., Pinecone, Weaviate, pgvector, or equivalent) in a production enterprise environment
Prior exposure to data mesh or data product operating model frameworks and experience translating those principles into practical platform and governance decisions
Preferred Skills: Current Employees apply HERE Current Contingent Workers apply HERE
San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance
Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance
Search Firm Representatives Please Read Carefully Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company. No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails.

Responsibilities

Serve as the champion for Data Architecture & Engineering excellence, leading the modernization of data infrastructure, embedding GenAI solutions, and ensuring the resilience of commercial data platforms to support the DHH organization.
Lead Specialized Teams: Direct and oversee four core capability areas: Data Quality & Business Rules Management, Innovation Capabilities, Data Operations, and Foundational Capabilities.
Roadmap Execution: Translate the organization's GenAI and modernization ambitions into prioritized, executable technical and engineering roadmaps.
Role Model Leadership: Demonstrate senior leadership behaviors including cross-functional leadership, swift decision-making, strategic thinking, and fostering a culture of technical innovation.
GenAI-Ready Architecture: Architect and oversee the design of GenAI-ready data infrastructure, including curated semantic layers, vector store implementations, and Retrieval-Augmented Generation (RAG) pipelines.
Pilot to Production: Lead the Innovation Capabilities team in evaluating, piloting, and productionizing GenAI solutions to increase enterprise GenAI fluency and adoption.
Legacy-to-Modern Migration: Direct the Foundational Capabilities team in executing legacy-to-modern platform migrations and building future-proof, scalable architectural foundations.
Architecture Standards: Champion and enforce enterprise data architecture standards, including cloud-native design patterns, composable data product architecture, and API-first data access.
Data Operations Lifecycle: Lead the Data Operations team to ensure steady-state platform operations, high availability, rapid incident response, and strict SLA adherence.
Automated Data Quality: Oversee the Data Quality & Business Rules Management team to implement and scale an automated Data Quality (DQ) framework across all data tiers.