Senior Data Engineer - London
3 weeks ago
Job summary
Ready to revolutionize healthcare, making it faster and more accessible than ever before? How we started: Back in 2013, our founder Dwayne D'Souza saw an opportunity to give people faster and more convenient access to medications using technology. We've grown rapidly since our inception, without any external funding whatsoever – achieving profitability through innovation and a highly disciplined approach to growth. Where we are now: We've earned the trust of millions of people worldwide through our top-selling products and well-known brands: MedExpress, Dermatica, ZipHealth, RocketRX, and Levity. A lot of our success is down to having our own pharmacies, manufacturers and products – spearheaded by leading in-house medical teams, researchers and pharmacists. Between 2023 and 2024 our global revenue tripled; £60m to £180m (300% year-on-year growth). We're looking to do the same in 2025; move into new territories, and further accelerate our growth journey. There's never been a more exciting time to join HeliosX.
Responsibilities
- Design and Build Enterprise-Scale Pipelines: Lead the design and implementation of complex, end-to-end batch and streaming data pipelines, including advanced transformation logic and multi-source data integration.
- Implement MLOps and Feature Stores: Build infrastructure for end-to-end ML pipelines, including feature engineering, model deployment, monitoring, and designing feature stores for both batch and real-time ML workflows.
- Establish DataOps Practices: Set up CI/CD, automated testing, deployment, and monitoring frameworks for data pipelines, managing infrastructure as code, and ensuring comprehensive pipeline observability.
- Technical Leadership: Influence engineering architecture across multiple product squads, establish data engineering practices, and mentor junior/mid-level data engineers within the organization.
- Ensure Data Governance and Quality: Establish data governance frameworks, build automated data quality systems, and maintain reliability and compliance across distributed systems.
- Optimize Performance and Resources: Continuously optimize compute and storage resources and deliver improvements in pipeline performance and cost efficiency.
Job description
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