About the Company
Cpl UK Life Sciences is a specialist recruitment partner focused on connecting highly skilled professionals with leading organizations across the life sciences sector. With strong market expertise across the UK, Switzerland, Europe, and the USA, the company supports a wide range of clients from global pharmaceutical leaders to innovative biotech startups.
The organization delivers end-to-end talent solutions across multiple hiring models, including permanent, contract and temporary roles, FSP (functional service provider), embedded multi-hire teams, and executive search.
About the Role
This is a Data Engineer position focused on building scalable data pipelines and supporting analytics within a high-performing data environment. The role involves working with large datasets, designing efficient data workflows, and enabling data-driven decision-making across business functions.
Responsibilities
- Design, develop, and optimize scalable data pipelines (batch and streaming)
- Ingest, transform, and structure data from multiple sources
- Build and maintain robust data models for reporting and analytics
- Implement big data solutions using tools such as Spark, EMR, Redshift, and Kinesis
- Develop infrastructure-as-code solutions using AWS CDK
- Build automated data quality frameworks ensuring accuracy and reliability
- Write high-performance SQL for complex data transformations
- Collaborate with engineering and business teams to deliver data solutions
- Improve performance, scalability, and cost efficiency of data systems
Requirements
- Strong experience building and maintaining data pipelines at scale
- Solid background in data modelling, ETL/ELT, and data warehousing
- Proficiency in SQL and at least one programming language (Python, Java, or Scala)
- Experience working with large-scale distributed data systems
- Strong understanding of software engineering practices including CI/CD, testing, and version control
Nice to Have
- Experience with AWS services such as S3, Glue, Redshift, EMR, Kinesis, and Lambda
- Exposure to Spark or similar big data frameworks
- Experience with non-relational databases and modern data storage systems
Benefits
- Opportunity to work with leading life sciences organizations
- Exposure to large-scale, modern data engineering environments
- Hybrid or flexible working models depending on assignment
- Work within high-impact data and analytics teams
- Access to complex and diverse datasets across global projects