Manager - Digital and Technology, Core Finance Data Engineer
Pfizer
Accounting & Finance, Software Engineering, IT, Data Science
Posted on Mar 10, 2026
Basic Qualifications
Information & Business Tech
- Bachelor’s degree in computer science, Information Technology, or similar field
- Experience working with on‑premises and cloud‑based data platforms (e.g., AWS, Azure, or hybrid environments).
- Experience working with modern cloud data platforms and warehouses, such as Snowflake, Microsoft Fabric, or equivalent technologies.
- Hands‑on experience with relational database technologies, including Aurora, PostgreSQL, Oracle, or similar enterprise databases.
- Familiarity with data quality, monitoring, and operational best practices for production workloads.
- Experience with ETL Tools (AWS Glue, Informatica, Talend, etc.)
- Experience implementing CI/CD pipelines for data workloads using tools such as Git, Azure DevOps, or GitHub Actions.
- Exposure to AI‑enabled or automation techniques applied to data engineering (e.g., accelerating analysis, improving data quality, or supporting scalable processing).
- Ability to produce clear technical documentation and collaborate effectively with cross‑functional stakeholders
- Excellent written and verbal communication skills
- Excellent organizational and time management capabilities
- Strong interpersonal skills in building customer relationships
- Ability to work independently and in a global team setting across time zones.
- Exposure to DevOps practices, including automation, deployment, and operational support.
- Working knowledge of Power BI, including supporting analytics and reporting use cases.
- Cloud certification or equivalent hands‑on experience with AWS and/or Azure.
- Experience or familiarity with React for building or integrating web‑based applications.
- Pharmaceutical life science domain experience
- Design and Implement data models to support large scale business intelligence reporting
- Drive harmonization of data definitions, transformations, and reusable components across platforms.
- Identify gaps and improvement opportunities (quality, performance, reliability) and propose remediation actions.
- Design and build end-to-end data pipelines and curated datasets across on‑prem and cloud environments.
- Operate and support production workloads with monitoring, logging, and operational best practices.
- Apply AI where it adds value (e.g., accelerating analysis, improving data quality, enabling scalable processing).
- Maintain clear technical documentation (data flows, specs, operational notes) and collaborate with stakeholders to align with standards
- Contribute to CI/CD pipelines and automated strategies.
- Collaborate and partner across high-performing, cross-functional software engineering teams
- Partner with stakeholders to translate business needs into technical solutions
- Model ownership behaviors and accountability for team outcomes.
Information & Business Tech
