Cloud Data Engineer

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.

Key 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