Manager, Data Specialist

PfizerCollegeville, PA
$99,200 - $165,400Hybrid

About The Position

The AI Acceleration (AIA) function within the Chief Marketing Office (CMO) is the single, business-led engine that owns the design, delivery, and scale-up of priority AI capabilities across Commercial operations. AIA works in tight collaboration with various Pfizer functions to deploy and maintain production-grade AI solutions that simplify how we work and drive measurable value across all processes. The Manager, Data Specialist will serve as a critical bridge between business stakeholders and the data engineering team. This role will be responsible for deeply understanding commercial business processes, translating complex analytical and AI/ML requirements into actionable data engineering specifications, and ensuring the delivery of high-quality, governed data products that power commercial insights and AI-driven decision-making. The Manager, Data Specialist will partner closely with business translators, commercial analytics leads, data scientists, and AI/ML engineers to define data needs, validate data availability, and ensure that the data engineering team is building solutions that are fit for purpose, well-documented, and aligned to enterprise data governance standards.

Requirements

  • Applicant must have a bachelor's degree with at least 4 years of experience; OR a master's degree with at least 2 years of experience; OR a PhD with 0+ years of experience; OR as associate's degree with 8 years of experience; OR a high school diploma (or equivalent) and 10 years of relevant experience.
  • Experience in a data-focused role such as business analyst, data analyst, data product manager, or comparable function within a data-intensive organization.
  • Demonstrated experience translating business requirements into technical specifications for data engineering or BI/analytics development teams.
  • Experience in the pharmaceutical, biotech, or life sciences industry, particularly within a commercial analytics or sales operations function.
  • Familiarity with commercial pharma data sources such as IQVIA (APLD, NPA, NSP), Symphony Health, Veeva CRM, patient claims data, or HCP/HCO affiliation data.
  • Working knowledge of relational data concepts, SQL, and data warehousing/lakehouse architectures (e.g., Snowflake, Databricks, Redshift).
  • Familiarity with data pipeline development concepts (ETL/ELT), data modeling, and data quality frameworks.
  • Experience working within an Agile/Scrum delivery model; proficiency with tools such as Jira, Confluence, or equivalent.
  • Strong written and verbal communication skills with the ability to interface effectively with both technical and non-technical audiences.
  • Permanent work authorization in the United States.

Nice To Haves

  • Bachelor's degree in a quantitative, analytical, or business discipline (e.g., Data Science, Information Systems, Statistics, Business Analytics).
  • 5+ years of experience in a data-focused role such as business analyst, data analyst, data product manager, or comparable function within a data-intensive organization.

Responsibilities

  • Engage directly with commercial business stakeholders—including Brand, Sales Operations, Market Access, Content Generation, and Medical —to elicit, clarify, and document data and analytics requirements.
  • Decompose high-level business needs into structured data engineering work items including data product definitions, pipeline specifications, transformation logic, and acceptance criteria.
  • Facilitate working sessions between business users and engineering teams to align on scope, timelines, and technical feasibility.
  • Serve as the primary point of contact for data-related inquiries from commercial analytics and AI/ML teams, triaging requests and ensuring efficient backlog management.
  • Author detailed data product specifications including source-to-target mappings, business rules, data dictionaries, and field-level definitions.
  • Define and document data quality expectations, validation rules, and SLA requirements in collaboration with data engineering and governance teams.
  • Maintain and continuously improve data documentation artifacts within the enterprise data catalog to support self-service discovery and AI-readiness.
  • Partner with data architects to ensure proposed data products align with the enterprise semantic layer and are optimized for downstream AI/ML and analytics consumption.
  • Translate prioritized business requirements into well-defined user stories, epics, and technical tasks within the data engineering development backlog.
  • Collaborate with data engineers to refine tickets, clarify ambiguities, and provide domain context that enables efficient, high-quality delivery.
  • Track progress of data engineering deliverables, identify blockers, and communicate status and impacts to business stakeholders in a clear, non-technical manner.
  • Validate delivered data products against requirements and coordinate user acceptance testing with business teams prior to production release.
  • Champion data quality by defining, monitoring, and communicating metrics that measure the reliability, completeness, and timeliness of commercial data assets.
  • Work with data governance and compliance teams to ensure data products adhere to applicable privacy, regulatory, and data stewardship standards relevant to commercial pharma (e.g., IQVIA, CRM, HCP/HCO data).
  • Identify and document data lineage, ownership, and usage policies for commercial data domains.
  • Understand and support the data requirements of AI/ML and advanced analytics use cases, including feature engineering inputs, model training datasets, and inferencing pipelines.
  • Coordinate with data scientists and ML engineers to ensure data products are structured, enriched, and accessible in formats optimized for model development and deployment.
  • Contribute to the continuous improvement of data standards that ensure commercial AI initiatives are built on a trusted, governed data foundation.

Benefits

  • 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution
  • paid vacation, holiday and personal days
  • paid caregiver/parental and medical leave
  • health benefits to include medical, prescription drug, dental and vision coverage
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