Junior Data Engineer

Role Overview

This role is for engineers at the start of their career, including final-year students, recent graduates and engineers with up to roughly two years' experience.

Join a delivery team building cloud-native data platforms on AWS and Azure, using Databricks and Microsoft Fabric. You will work on client systems from early on, writing pipelines, fixing data-quality problems and getting work into production with a Senior Engineer alongside you.

Responsibilities

• Build and maintain data pipelines in Python, PySpark and SQL under the guidance of a senior engineer.
• Work with data across the lifecycle: ingesting it from source systems, transforming it, modelling it and making it usable for reporting, analytics and AI.
• Write production code using version control, peer review and delivery practices.
• Investigate and fix pipeline failures and data-quality issues and learn to distinguish symptoms from causes.
• Document what you build so that other engineers can maintain it.
• Take part in code reviews, stand-ups, design discussions and client delivery.
• Develop exposure to lakehouse platforms, cloud data services, data modelling, orchestration, monitoring, infrastructure practices and client communication.

Requirements

• Bachelor's degree completed or in the final year in Engineering, Computer Science or a related field.
• Working knowledge of Python and SQL, including non-trivial scripts, joins and aggregations.
• Solid programming fundamentals, problem-solving instincts and persistence.
• Evidence of building things through university projects, personal projects, internships, hackathons or coursework.
• Clear written and verbal communication in English and a genuine interest in data, cloud and AI.
• Willingness to travel to clients when required.
• Cloud, Databricks, Spark, Microsoft Fabric, Power BI, dbt, Git, Linux or Docker exposure is advantageous.