Manager, Data and Analytics Engineer
Explicitly requires vibe coding experience and building Generative AI–based data pipelines and analytics solutions.
About the Role
Pfizer is hiring a hands-on Manager, Data & Analytics Engineer to lead a team building scalable data pipelines, data architectures, governance and analytics solutions for enabling functions (HR, Finance, GBS, Legal). The role combines technical ownership of cloud-based data systems, data governance, vendor management and mentorship to deliver accurate business insights and support data-driven decisions.
Job Description
Role
Hands-on Manager, Data & Analytics Engineer responsible for leading and building scalable data pipelines, designing data architecture and infrastructure, establishing data governance, and delivering analytics solutions that support enabling functions (HR, Finance, Global Business Services, Legal).
Key Responsibilities
- Build scalable data pipelines and ETL processes to deliver accurate business analytics and insights.
- Design and implement data architecture and infrastructure across platforms.
- Lead and manage a team of project data engineers and analysts; provide guidance and mentorship.
- Develop and enforce data management strategies, policies, data governance frameworks, documentation and metadata practices.
- Ensure data quality, integrity, security and compliance with privacy regulations.
- Integrate new data technologies and tools; oversee performance, scalability and optimization of data systems and workflows.
- Develop analytics solutions, monitor KPIs for data initiatives, and manage relationships with external data vendors and partners.
Required Qualifications
- Bachelor’s degree (MBA/MS/M.Tech) with 5–10 years relevant experience, or PhD with any years of relevant experience.
- Expert-level experience in data architecture design, data warehousing (preferably Snowflake), SQL, ETL/data pipelines, and data integration.
- Advanced experience with cloud platforms (AWS, Azure, Google Cloud) and big data technologies (Snowflake, Databricks, Spark).
- Proficiency in data modeling, BI/visual analytics (Tableau, Power BI), data governance, data quality management and data visualization.
- Programming experience with languages such as Python, R and SQL (6+ years with one or more data processing languages including SQL, Scala, Python, Java).
- Leadership, strategic planning, communication, collaboration and problem-solving skills.
- Hands-on experience with vibe coding and Generative AI–based data pipeline and analytics solution development.
Preferred Qualifications
- Experience with People Analytics and SaaS tools (Visier, One Model, Perceptyx, Workday Prism Analytics, Workday People Analytics, SAP SuccessFactors Workforce Analytics) and familiarity with Workday/HCM systems.
- Experience with global HR data integration, M&A-related data activities, GDPR/SoX and privacy-by-design data architecture.
- Familiarity with software engineering best practices (version control such as Git/GitHub, TFS, Subversion; CI/CD tools like Jenkins, Maven, Gradle; automated testing; DevOps).
- Experience publishing data and analytics services via APIs, working in Agile/SCRUM/SAFe environments, and applying ML/NLP/text analysis or recommendation engines is a plus.
Technical & Tools
Explicitly referenced technologies and tools include Snowflake, Databricks, Spark, AWS, Azure, Google Cloud, Tableau, Power BI, Visier, One Model, Perceptyx, Workday Prism Analytics, Workday People Analytics, SAP SuccessFactors Workforce Analytics, Workday, Git, GitHub, TFS, Subversion, Jenkins, Maven, Gradle, Python, R, SQL, Scala, Java, Generative AI, NLP, APIs, CI/CD and DevOps practices.
Work Location
Work Location Assignment: Hybrid