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- Tasks: Lead the design and build of automated data pipelines using AWS services.
- Company: Join Chemist4U, one of the UK's largest online pharmacies, revolutionising healthcare access.
- Benefits: Enjoy a full-time role with opportunities for remote work and professional growth.
- Why this job: Shape data strategies that impact healthcare decisions and improve lives.
- Qualifications: 5+ years in data engineering with strong AWS experience required.
- Other info: Ideal for tech-savvy individuals passionate about data and healthcare innovation.
The predicted salary is between 43200 - 72000 ÂŁ per year.
Direct message the job poster from Chemist4U
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.
Seniority level
-
Seniority level
Mid-Senior level
Employment type
-
Employment type
Full-time
Job function
-
Job function
Information Technology
-
Industries
Retail
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Senior Data Engineer (AWS) employer: Chemist4U
Contact Detail:
Chemist4U Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Engineer (AWS)
✨Tip Number 1
Familiarise yourself with AWS services, especially Glue, Athena, and Lambda. Being able to discuss specific projects or experiences where you've used these tools will show your expertise and make you stand out.
✨Tip Number 2
Prepare to discuss data quality and governance practices. Highlight any experience you have with automated data validation and compliance with standards like GDPR, as this is crucial for the role.
✨Tip Number 3
Showcase your understanding of data modelling principles. Be ready to explain how you've applied concepts like partitioning and denormalisation in past projects to improve performance and maintainability.
✨Tip Number 4
Demonstrate your collaborative skills by preparing examples of how you've worked with stakeholders to translate business needs into data solutions. This will highlight your ability to bridge the gap between technical and non-technical teams.
We think you need these skills to ace Senior Data Engineer (AWS)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with AWS services like Glue, Athena, and Lambda. Use specific examples to demonstrate your skills in building ETL pipelines and managing data quality.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data engineering and how your background aligns with Chemist4U's mission. Mention your experience with data architecture and governance, and how you can contribute to their modern data platform.
Showcase Relevant Projects: If you have worked on projects that involved AWS data services or similar technologies, be sure to include these in your application. Describe the challenges you faced and how you overcame them, focusing on performance and cost optimisation.
Highlight Continuous Improvement Efforts: Discuss any initiatives you've led or participated in that promote documentation, standardisation, or operational excellence in data workflows. This will show your commitment to continuous improvement, which is key for the role.
How to prepare for a job interview at Chemist4U
✨Showcase Your AWS Expertise
Make sure to highlight your hands-on experience with AWS services like Glue, Athena, and Lambda. Be prepared to discuss specific projects where you implemented these technologies and the impact they had on data processing and analytics.
✨Demonstrate Data Quality Knowledge
Since data quality is crucial for this role, be ready to explain how you've implemented data validation, anomaly detection, and compliance measures in past projects. Use examples to illustrate your understanding of data governance and best practices.
✨Discuss Performance Optimisation Strategies
Prepare to talk about how you've optimised ETL pipelines for performance and cost efficiency. Share any experiences you have with tuning query layers and decommissioning underutilised resources, as this will show your ability to enhance operational efficiency.
✨Engage in Stakeholder Collaboration
Highlight your experience in translating business requirements into technical solutions. Discuss how you've collaborated with analysts and stakeholders to create resilient data products, as this role requires strong communication and teamwork skills.