Senior Data Engineer

Pfizer is hiring a Senior Data Engineer. Level rates it ; you can apply on Pfizer.

Level's read on this job

On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
Tools and skills the posting cites include Informatica Iics, SQL and AWS.
Level classifies it as a senior role.
Level lists 608 other open roles at Pfizer.
The role was posted in the last few days.

AI in this role

Operate, monitor, and troubleshoot enterprise data lakes, ETL pipelines, and data integration platforms.

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data-engineeringetldata-lakeproduction-supportdata-pipelines

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.

Work Location Assignment: On Premise

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.

Information & Business Tech

How we rate this

Senior Data Engineer at Pfizer rates 0 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Data Engineer is an open job at Pfizer.
Level rates this role AI Level 1 of 4: Little AI.
The role is based in China - Zhejiang - Hangzhou.
The job was posted on October 29, 2026.
Seniority: senior.
Applications are handled by Pfizer. Apply on Pfizer

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Data EngineeringETLData LakeProduction SupportData PipelinesInformatica IicsSQLAWS

Also common in data engineer jobs at this level

Spark Azure Airflow Databricks Google Cloud Java

Pay

Typical data engineer job: $150k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data lake was part of your work. What did you do?
Tell me about a project where production support was part of your work. What did you do?
Tell me about a project where data pipelines was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Engineering, ETL, Data Lake, Production Support, and Data Pipelines. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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