Manager - HR & Corporate Functions Data & Analytics Engineering

Role Summary

Manager - HR & Corporate Functions Data & Analytics Engineering

The Enterprise Data Solutions and Engineering (EDSE) is responsible for the development and management of all data and analytics tools and platforms across the enterprise. You will design and deploy analytic solutions, lead high performing teams, and build relationships with business colleagues to produce the data foundation that drives insights through data science and enterprise BI reporting solutions. This role provides solution development and operations support for HR & Corporate Functions domains, leveraging your data analytics and HR domain experience to create innovative data and analytics products. You will lead a group of vendor resources and collaborate with Digital Colleagues, Enterprise Architecture, and Business Unit stakeholders to develop and sustain the HR & Corporate Functions data strategy and target data architecture. You will help architect, design, and build data models, pipelines, and products across domains to power ML ops platforms, data-driven applications, and BI solutions.

You will work with business leadership to understand needs where AI/ML can yield new products and services and enhance processes. You will embody Pfizer’s OWNIT! culture values, think differently, take calculated risks, and deliver commitments with speed, decisiveness, and integrity.

Responsibilities

• Responsible for people data engineering, architecture, data modeling, building/enhancing data pipelines, and visualizations to drive outcomes.
• Maintain and enhance on-premise and cloud HR & Corporate Functions data lakes, Informatica PowerCenter data flows, Oracle RDBMS, Snowflake ELT, Unix shell scripts, Business Objects, Tableau, and People Analytics visualizations.
• Manage and oversee a team of vendor developers delivering enhancements within HR, Learning, Legal, Compliance, and Corporate Affairs; ensure adherence to data engineering practices and standards.
• Design automated solutions for building, testing, monitoring, and deploying ETL/ELT solutions.
• Analyze existing and new data sources and systems to enable intuitive data consumption and understanding.
• Coordinate with source systems engineering to improve efficiency, performance, data quality, and data consistency.
• Perform root cause analysis and resolve Level 3 production and data issues.
• Create and validate test plans and data validation; tune SQL queries, reports, and ETL pipelines.
• Build and maintain data dictionary and process documentation.
• Present solutions to leadership, management, architects, and developers.
• Lead cloud data engineering staff and partner with PMs and analysts to deliver insights.
• Provide hands-on technical and thought leadership; mentor across teams.
• Apply analytical/problem-solving experience with large-scale platforms and infrastructure.
• Collaborate with Analytics enablement teams to deploy new analytics capabilities to democratize data within HR & Corporate Functions.

Qualifications

• BS/MS in Computer Science, Engineering, Information Systems or related field.
• Experience in HR with focus on People Data & People Data Engineering, HR Reporting, and Workforce Analytics.
• Strong experience in Informatica PowerCenter, IICS, Snowflake, Oracle RDBMS, Unix shell scripting, Python, etc.
• 5+ years in data warehousing, data modeling, and data transformation.
• 5+ years as a Data Engineer; 3+ years as a Data Solution Architect.
• Hands-on experience with AI/Generative AI-based data pipelines and analytics solutions development.
• Experience with AirFlow, Snowflake, and modern ETL/ELT development.
• Deep understanding of cloud data warehouses (Snowflake, Redshift, Spark) and AWS/GCP stack.
• 5+ years designing complex data models for analytics and ML use cases.
• Proven project management experience with data engineering and analytics budgets ($200K‚Äì$1MM annually).

Preferred Qualifications

• People Analytics experience using SaaS tools (Visier, One Model, Perceptyx, Workday Prism Analytics, Workday People Analytics, SAP Success Factors Workforce Analytics); familiarity with Workday HCM systems.
• Experience with Global HR data integration and M&A/Divestitures.
• Knowledge of GDPR and data privacy principles; prior data architecture for GDPR.
• Experience with software engineering practices (version control, CI/CD, automated testing, DevOps).
• Experience with APIs for data publishing; data services; agile methodologies (SCRUM/SAFe).
• 5+ years in general-purpose data processing languages (SQL, Scala, Python, Java).
• Experience architecting end-to-end data pipelines on major cloud stacks; ML/AI service development.

Education

• BS/MS degree in Computer Science, Engineering, Information Systems or related field.

Additional Requirements

• Location: Hybrid.