Platform Data Engineer

£500-£600 per day

Outside IR35

6-months

Join one of the UK's leading online retailers as they evolve their next-generation data platform. This is an opportunity to shape the backbone of a modern data ecosystem, empowering analysts, ML engineers, and data scientists to deliver smarter, faster insights at scale.

You'll play a key role in designing and engineering platform services that treat data as a core product. This means building scalable, secure, and observable systems that help teams confidently leverage data across the business.

You'll work closely with a wide range of technical and non-technical partners to deliver resilient infrastructure, champion data governance, and mentor others in engineering excellence.

In this role, you will:

• Shape the data platform roadmap: Introduce modern observability, quality, and governance frameworks that elevate how teams access and trust data.

• Build and scale infrastructure: Develop services, APIs, and data pipelines using modern cloud tooling and automation-first principles.

• Drive engineering best practices: Implement CI/CD pipelines, testing frameworks, and container-based deployments to ensure reliability and repeatability.

• Lead cross-functional initiatives: Collaborate with product engineers, data scientists, and ML practitioners to understand their workflows and deliver high-impact platform solutions.

• Champion operational reliability: Proactively monitor system performance, automate incident response, and strengthen platform resilience.

• Strong proficiency in Python (or a similar high-level language) with a deep understanding of software engineering best practices - testing, automation, clean code, and CI/CD.

• Proven track record building and maintaining scalable data platforms in production, enabling advanced users such as ML and analytics engineers.

• Hands-on experience with modern data stack tools - Airflow, DBT, Databricks, and data catalogue/observability solutions like Monte Carlo, Atlan, or DataHub.

• Solid understanding of cloud environments (AWS or GCP), including IAM, S3, ECS, RDS, or equivalent services.

• Experience implementing Infrastructure as Code (Terraform) and CI/CD pipelines (e.g., Jenkins, GitHub Actions).

• A mindset focused on continuous improvement, learning, and staying at the forefront of emerging technologies.

• Experience rolling out data governance and observability frameworks, including lineage tracking, SLAs, and data quality monitoring.

• Familiarity with modern data lake table formats such as Delta Lake, Iceberg, or Hudi.

• Background in stream processing (Kafka, Flink, or similar ecosystems).

• Exposure to containerisation and orchestration technologies such as Docker and Kubernetes.