Overview

Purpose of the Role: To design, build, and maintain the systems that collect, process, and analyse data - including pipelines, data warehouses, and data lakes - ensuring data is accurate, accessible, and secure.

Responsibilities

• Develop, maintain, and optimise scalable data pipelines and data storage solutions.
• Design and implement data warehousing and data lake architectures.
• Ensure robust data governance, security, and compliance across all systems.
• Collaborate with cross-functional teams to gather requirements and deliver solutions that support business objectives.
• Apply machine learning and data mining techniques where appropriate to add value.
• Support change and transformation initiatives by providing reliable data systems.
• Identify risks, implement controls, and follow secure coding practices.
• Provide strategic input on data architecture, technology adoption, and best practices.

Skills & Competencies

• Strong knowledge of database structures, data modelling, and data engineering practices.
• Proficiency in requirements analysis, problem-solving, and strategic thinking.
• Ability to work collaboratively with technical and non-technical stakeholders.
• Business acumen with a focus on delivering data-driven value.
• Strong understanding of risk, controls, and compliance in data management.

Technical Skills

• Hands-on experience with Python, PySpark, and SQL.
• Experience with AWS (preferred).
• Knowledge of data warehousing (DW) concepts and ETL processes.
• Familiarity with DevOps principles and secure coding practices.

Experience

• Proven track record in data engineering, data governance, and large-scale data systems.
• Experience working on change and transformation projects.
• Background in applying machine learning or data mining is an advantage