Senior Data Engineer

Role Overview

We are looking for an experienced Senior Data Engineer to support the reliable operation and continuous improvement of our enterprise Data Lake and data integration platforms.

This is a hands-on engineering role with a strong focus on Data Lake BAU operations, production support, data pipeline reliability, and troubleshooting. The ideal candidate will have solid data engineering expertise, strong problem-solving skills, and a detail-oriented, patient, and ownership-driven mindset.

Key Responsibilities

• Data Lake & Pipeline Operations
  Operate and monitor Data Lake services, ETL/ELT pipelines, scheduled jobs, data synchronization, ingestion, and downstream delivery to ensure data is processed accurately and on schedule.
• Production Support & Troubleshooting
  Provide L2/L3 support and investigate job failures, missing/rejected data, synchronization delays, data discrepancies, performance, and integration issues. Perform root cause analysis across source systems, data pipelines, Data Lake, and downstream applications.
• Data Quality & Operational Readiness
  Support data quality monitoring, reconciliation, access management, security and audit activities, platform maintenance, Disaster Recovery, and production readiness.
• Change, Release & Engineering Enhancement
  Support platform changes, releases, configuration updates, bug fixes, and integration changes. Develop or enhance ETL/ELT pipelines, SQL logic, mappings, and data processing components where required.
• Continuous Improvement & Collaboration
  Automate repetitive BAU activities, improve monitoring and platform reliability, maintain SOPs/runbooks, and collaborate with Data Engineering, Product, Infrastructure, upstream/downstream teams, and technology partners.

Qualifications & Technical Skills

Required

• 6+ years of experience in Data Engineering, Data Integration, Data Platform Engineering, or ETL/ELT development.
• Strong hands-on experience with SQL, ETL/ELT, data pipelines, Data Lake, data warehouse, and data integration.
• Experience with enterprise ETL/data integration platforms. Informatica IICS or equivalent experience is highly desirable.
• Experience with cloud data platforms, preferably AWS/S3, and relational databases.
• Strong ability to troubleshoot complex production issues across data pipelines, databases, integrations, and upstream/downstream systems.
• Experience supporting business-critical production data environments, including monitoring, incident resolution, change/release, and production validation.
• Working knowledge of Python, Shell/Bash, or similar scripting and automation technologies.
• Strong analytical and problem-solving skills with a detail-oriented, patient, and ownership-driven working style.
• Good communication and collaboration skills with both technical and business stakeholders.

Preferred

• Hands-on experience with Informatica IICS, AWS S3, Redshift, PostgreSQL, Snowflake, or similar technologies.
• Experience with data quality, reconciliation, metadata, data lineage, and monitoring.
• Experience with CI/CD, automation, and DevOps practices for data engineering.
• Familiarity with enterprise Incident, Problem, Change, Release, Security, Audit, and Disaster Recovery processes.
• Experience in pharmaceutical, healthcare, life sciences, or other regulated industries is highly preferred.

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.