Senior Data Engineer

Senior Data Engineer

Job type:

Contract — 12-month initial

Salary:

Competitive hourly rate (DOE)

Role Location:

100% Remote (US-based candidates only)

The Company

Our client is a US-based pharmaceutical organization investing in its data infrastructure to support analytics, reporting and decision-making across the business. They're building out a modern data platform to serve research, commercial and operational teams.

They're looking for a Senior Data Engineer to design and build scalable data pipelines and infrastructure — initially engaged on a 12-month contract with strong potential to extend.

Role and Responsibilities

Design, build and maintain scalable data pipelines to ingest, transform and serve data across the business.

Develop and optimize data models supporting analytics, reporting and downstream applications.

Build and maintain ETL/ELT processes across a modern data stack.

Ensure data quality, integrity and governance across pipelines, appropriate for a regulated pharma environment.

Partner with data scientists, analysts and business stakeholders to understand data needs and deliver reliable datasets.

Monitor, troubleshoot and improve performance of existing data infrastructure.

Contribute to architecture decisions around data storage, processing and platform tooling.

Document data flows, pipelines and technical decisions to support audit and compliance requirements.

Job Requirements

Proven experience as a Senior Data Engineer building and maintaining production data pipelines at scale.

Strong SQL skills and experience with modern data platforms (e.g. Snowflake, Databricks, or similar).

Experience with ETL/ELT tools and orchestration frameworks (e.g. Airflow, dbt, or similar).

Strong Python or equivalent programming experience.

Experience with cloud data platforms (AWS, Azure or GCP).

Excellent communication skills, comfortable working with both technical and business stakeholders.

Must be based in the US and able to work US business hours.

Nice To Have

Experience within pharmaceutical, life sciences or other regulated industries.

Experience with real-time/streaming data pipelines (e.g. Kafka, Kinesis).

Familiarity with data governance and compliance frameworks relevant to regulated industries.