Data Engineer

The Role

As a Data Engineer, you’ll work within multidisciplinary teams alongside clients, designers, analysts and engineers to deliver modern data solutions. You’ll help design and build data pipelines, models and analytics products, learning from experienced colleagues and applying best practices as you go.

This is a hands‑on role where you’ll grow your technical skills, work closely with others, and gain experience delivering solutions that function in real‑world environments.

SC Clearance is a key requirement for this role. Candidates should ideally hold active SC clearance or be eligible and willing to undergo the clearance process.

What You’ll Do

• Help translate business problems into data, analytical and technical tasks, with support from senior colleagues.
• Design, build and maintain data pipelines, models and products using SQL, Python and modern data engineering tools.
• Work with data warehouses, lakehouse platforms and event‑driven patterns, including building semantic models for analytics and visualisation.
• Contribute to solutions built on cloud data and AI platforms (AWS/Azure), following sound software engineering, testing and CI/CD practices.
• Apply analytics, experimentation, AI/ML integration, governance, security and data quality practices as part of delivery teams.
• Create clear data visualisations and explanations that help users understand and act on insights.
• Work closely with users and stakeholders in Agile, client‑driven environments, learning from live services and user feedback.
• Follow relevant industry and government standards, contributing to solutions that are well documented, maintainable and easy to hand over.

What We’re Looking For

Core Data & Technical Skills

• Experience translating business questions into data or analytical requirements, with guidance where needed.
• Strong SQL and Python skills for data modelling, transformation, automation and analysis.
• Experience working with data models in data warehouses, lakehouse environments or analytics tools such as Power BI.
• Familiarity with modern data engineering frameworks and tools (e.g. Spark/PySpark, Pandas, orchestration tools).
• Experience with cloud data platforms on AWS or Azure (e.g. Databricks, Redshift, Microsoft Fabric).
• Understanding of software engineering fundamentals, including Git, testing, CI/CD and modular design.
• Basic analytics and statistical understanding, including metrics and simple experimentation.
• Awareness of AI/ML concepts, such as using model APIs or prompts, with a desire to build experience in this area.
• Understanding of data governance, security and quality concepts, including access control and GDPR considerations.
• Experience communicating insights through data visualisation using tools like Power BI, Tableau or Python charts.

Consulting & Delivery Mindset

• A user‑focused approach and curiosity about who will use the solution and why it matters.
• Ability to communicate clearly and collaborate effectively in client‑driven, sometimes ambiguous environments.
• Willingness to contribute to clear slides and written materials, with support and guidance.
• A logical, thoughtful approach to problem solving and delivery.
• Experience contributing to production systems or live services, with an interest in learning from user feedback.
• Attention to detail in code, documentation and naming conventions.
• A product mindset, with experience working in Agile teams delivering features and outcomes iteratively.
• Awareness of industry and government standards, and openness to learning and applying them in delivery.