Data Engineer
Role details
Job location
Tech stack
Job description
The purpose of the role is to design, build, and manage scalable data solutions focusing on the ingestion, transformation, and management of large datasets across and real-time analytics environments. This includes developing robust and efficient data pipelines, ensuring secure and well-governed data access, and optimising system performance.
The role also involves analysing business requirements to ensure data is accessible and usable for decision-making, while carrying out platform administration, monitoring, and maintenance to support reliable and secure operations.
MAIN RESPONSIBILITIES:
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Develop and maintain data infrastructure, data warehouses, and big data processing systems.
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Build data pipelines that clean, transform, and aggregate data from disparate sources.
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Build solutions for automated ingestion and data versioning i.e. Time Travel.
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Provide technical skills and support to other areas for Fabric components under the team's control.
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Ensure data accuracy, reliability, security, and compliance with policies.
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Work with analysis engineers, analysts, developers and business teams to understand needs and deliver solutions.
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Re-engineer manual processes for scalability and efficiency.
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Deliver project tasks to agreed timescales and provide technical expertise to ensure project success.
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Ensure business continuity strategy is appropriate for purpose and is always delivering.
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To perform established procedures to accredited standards on an ongoing basis.
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Contribute to the planning, research, recommendation, and implementation of current and future IT strategies.
Requirements
Essential
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Demonstrable experience of Spark (PySpark) and SQL.
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Demonstrable experience of Fabric components.
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Demonstrable experience of working on enterprise environments.
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Experience of designing architectural Fabric processes.
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Experience of Azure Data Factory.
Desirable
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DP-700 (Microsoft Fabric Data Engineer) certification.
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Demonstrable experience of data visualization/exploration tools.
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Understanding of Project Life Cycles.
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Able to deliver innovative solutions for problems encountered within the scope of Data Engineer duties.
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Continuous improvements to existing team processes / monitoring.
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High attention to detail and ability to work under pressure.