Senior Data Engineer
Signify Technology
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.
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