8 hours ago
London, United KingdomSenior
Responsibilities
- Design and build data platform capabilities for data and machine learning workloads.
- Develop high-performance data pipelines and processing frameworks using Python, Scala, Spark, and Databricks.
- Own and evolve platform components supporting the development, testing, deployment, and monitoring of data products.
- Improve platform reliability, observability, data quality, and operational excellence.
- Create reusable libraries, tooling, and engineering patterns for data product teams.
- Partner with Data Scientists, ML Engineers, and Product Engineering teams to enable machine learning use cases.
- Contribute to architecture decisions, data engineering standards, and technical direction.
- Optimize distributed workloads for performance, scalability, and cost efficiency across Azure.
- Mentor engineers through technical guidance, code reviews, and knowledge sharing.
Requirements
- Experience building or operating large-scale data platforms or data-intensive applications in a cloud environment.
- Experience with Databricks, Spark, and distributed data processing technologies.
- Production-grade data engineering experience using Python and/or Scala.
- Experience designing data architectures for scalability, reliability, and cost efficiency.
- Experience with CI/CD, automated testing, observability, and Infrastructure as Code.
- Demonstrated ability to solve complex engineering problems and improve platform capabilities for other teams.
- Experience leading the design and delivery of complex data engineering solutions and contributing to technical direction and best practices.
- Ability to collaborate across teams and stakeholders while delivering scalable, reliable, and maintainable data solutions.
Benefits
- Employee discount and employee sample sales.
- 25 days of paid annual leave plus an additional celebration day.
- Discretionary bonus scheme.
- Private medical care scheme.
- Flexible benefits allowance that can be taken as extra cash or used for other benefits.
- Personalized learning and in-the-moment development experiences.
Tech Stack
Categories
Data Engineering
About ASOS
ASOS is a global online fashion and beauty retailer for 20‑somethings, selling own‑brand and third‑party labels via its website and mobile apps. The company earns revenue from direct‑to‑consumer e‑commerce, shipping to customers worldwide and offering marketplace services for brands. Founded in 2000 and headquartered in London, ASOS is a public company listed on the London Stock Exchange and runs in‑house content and fulfillment operations at scale.