IT & Software

Senior Data Engineer

hireful

London · Greater London · United Kingdom

Overview

As a Senior Data Engineer, you will own and shape a scalable data platform built on Databricks, delivering trusted data products and self-serve access for the business. You’ll work closely with cross-functional teams to translate challenges into data solutions and help mature the data function. This role offers visible impact on architecture and platform strategy in a growing data organisation. You’ll join a collaborative, hands-on team at a pivotal stage of our Data Ops journey.

Pay / Benefits
  • health insurance
  • income protection
  • life assurance
  • subsidised gym membership
  • 25 days' holiday plus birthday off
Responsibilities
  • Design, build and maintain scalable data pipelines and data products using Databricks, PySpark, Spark SQL and Delta Lake
  • Develop and optimise ETL/ELT processes to ingest, transform and curate data from internal and external systems
  • Shape enterprise data architecture balancing scalability, performance, security and maintainability
  • Partner with Finance, Product, Sales, Marketing and Engineering to translate business challenges into technical solutions
  • Embed data quality, governance and access controls throughout the data lifecycle
  • Mentor a junior engineer and help mature a growing data function
Key requirements
  • Senior level data engineering experience with strong Databricks skills (PySpark, Spark SQL, Delta Lake)
  • Advanced SQL and Python coding
  • Track record of building and optimising enterprise-scale data pipelines and ETL/ELT solutions
  • Solid grounding in data architecture, modelling and modern data platform design
  • Cloud experience (AWS preferred; Azure also acceptable) and familiarity with CI/CD and source control
  • Experience across multiple data pools, with focus on financial & sales / revenue data preferred
  • Stakeholder collaboration
  • Mentoring and team growth
  • Problem solving and adaptability
  • Databricks
  • PySpark
  • Spark SQL

Reference: WJ-747_30484907

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