Data Engineer

Overview

As a Data Engineer, you will design and maintain scalable data pipelines to process data from multiple sources. You will transform data across models and build reusable, reliable solutions using Python and engineering best practices. You’ll work with cloud platforms, Spark, and modern data architectures in a collaborative, Agile environment. Your work directly supports scalable data processing and analytics across the organization. This role offers the chance to shape data infrastructure on large-scale projects and collaborate with cross-functional teams.

Responsibilities

• Design, build and maintain scalable data pipelines
• Transform and standardise data across different data models
• Develop reusable, maintainable solutions using Python and software engineering best practices
• Work with cloud platforms, distributed processing technologies and modern data architectures
• Collaborate with engineers and stakeholders in an Agile environment

Key requirements

• Proven Data Engineering experience in complex, large-scale environments
• Strong Python skills and experience building data pipelines
• Experience with data modelling and transforming data between different formats
• Knowledge of cloud platforms, ideally Azure, alongside Spark and Databricks
• Familiarity with data storage technologies such as Parquet and Delta Lake
• Experience with Docker, Kubernetes, Git/GitHub and Linux/Unix environments
• Ability to contribute to shared codebases and collaborative development teams

• Collaboration with engineers and stakeholders
• Agile teamwork and communication
• Python
• Data pipelines
• Data modelling
• Azure cloud platform

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