Job Description
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:
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Develop, maintain, and optimise scalable data pipelines and data storage solutions.
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Design and implement data warehousing and data lake architectures.
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Ensure robust data governance, security, and compliance across all systems.
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Collaborate with cross-functional teams to gather requirements and deliver solutions that support business objectives.
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Apply machine learning and data mining techniques where appropriate to add value.
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Support change and transformation initiatives by providing reliable data systems.
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Identify risks, implement controls, and follow secure coding practices.
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Provide strategic input on data architecture, technology adoption, and best practices.
Skills & Competencies:
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Strong knowledge of database structures, data modelling, and data engineering practices.
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Proficiency in requirements analysis, problem-solving, and strategic thinking.
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Ability to work collaboratively with technical and non-technical stakeholders.
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Business acumen with a focus on delivering data-driven value.
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Strong understanding of risk, controls, and compliance in data management.
Technical Skills:
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Hands-on experience with Python, PySpark, and SQL.
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Experience with AWS (preferred).
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Knowledge of data warehousing (DW) concepts and ETL processes.
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Familiarity with DevOps principles and secure coding practices.
Experience:
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Proven track record in data engineering, data governance, and large-scale data systems.
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Experience working on change and transformation projects.
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Background in applying machine learning or data mining is an advantage.
