Senior Data Engineer (AWS)

Job Description
Company Description
Chemist4U is proud to be one of the UK's largest online pharmacies, processing over 180,000 prescriptions a month. We’re committed to making healthcare affordable, accessible, and convenient for everyone.
We simplify processes and medication management by leveraging cutting-edge technology and empowering our team. Whether through seamless online services or expert support, we ensure reliable and hassle-free healthcare so our customers can focus on their well-being.
Role Description
As a Senior Data Engineer , you’ll be the lead technical resource for Chemist4U’s modern data platform, helping to shape how data flows across the organisation. You’ll turn raw dispensing, e-commerce, and marketing data into clean, reliable, query-ready assets that drive decisions across pharmacy operations, commercial, and digital teams.
You'll design and build robust, automated data pipelines using AWS services like Glue, Athena, Lambda, and S3. You’ll enforce data quality SLA's, improve observability, utilise best practices in data engineering, and collaborate with analysts and stakeholders.
Responsibilities
Data Architecture: Design and maintain scalable, modular pipelines using AWS services (Glue, Lambda, Step Functions, S3), supporting ingestion, transformation, and storage across key business domains.
Data Quality & Governance: Implement automated data validation, anomaly detection, lineage, and auditability; enforce consistent naming, access controls, and compliance with GDPR and healthcare standards.
Performance & Cost Optimisation: Tune pipelines and query layers (Glue, Athena) for performance and cost efficiency; advise on modelling strategies and decommission underutilised resources.
DevOps & Automation: Manage infrastructure as code; automate CI/CD workflows for deployments and schema changes; maintain environment separation with rollback safety.
Stakeholder Collaboration: Translate business questions into resilient data products; guide analysts on BI best practices and participate in sprint and architecture processes.
Continuous Improvement: Promote documentation, standardisation, and reusability across data workflows; drive a culture of operational excellence and ongoing optimisation.
Qualifications
Degree in Computer Science, Data Engineering, or related field (or equivalent experience).
5+ years of experience in data engineering, with a focus on analytics and platform scalability.
Strong hands-on experience with AWS data services - particularly Glue, Athena, S3, Lambda, and Step Functions.
Solid understanding of data modelling principles for analytics - including partitioning, denormalisation, and file formats (e.g., Parquet, ORC).
Experience building and maintaining production-grade ETL pipelines with an emphasis on performance, quality, and maintainability.
AWS certification desirable - Data Engineer or similar.

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