Platform Data Engineer

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London / £500 - £600 day

INFO

Salary
SALARY:

£500 - £600

Location

LOCATION

London

Job Type
JOB TYPE

Contract

Senior Platform 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.


The Role

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.


What You'll Bring

  • 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.


Nice to Have

  • 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.

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