Data Engineer Manager
Perm
London
£75,000pa - £85,000pa
Role Summary
The Data Engineer Manager is responsible drive the design, development, and optimization of data solutions in the data infrastructure. In addition to fostering the growth of a skilled team, you will play a pivotal role in delivering the data applications, infrastructure, and services, ensuring they align with organizational goals and industry best practices.
As part of the Technology Hub the Data Engineer Manager will work very closely with all teams across the business. The role is instrumental in defining and upholding a clear vision for the integrity of data life cycle management aligning the strategic goal of becoming a centre of expertise. Additionally, it ensures stewardship of business data and technical architecture, fostering innovation and reliability across all data initiatives.
Key Responsibilities
Mentor the data engineering team to design and implement complex, tailored data solutions that support processing of high volumes of data across all schemes and applications.
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Establish and support the technical vision and strategy for a robust data architecture that aligns with the overall strategy, with a strong focus on ensuring security for all structured data.
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Establish and maintain robust operational support and monitoring systems to ensure the reliable performance of critical systems in live environments.
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Facilitate the adoption and implementation of continuous delivery practices while advocating for the use of cloud solutions.
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Design, implement, and optimize end-to-end data pipelines and solutions on Azure, ensuring data quality, reliability, and security throughout. Oversee the integration of both structured and unstructured data sources.
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Oversee project timelines, scope, and deliverables to ensure successful execution, while actively monitoring progress and addressing risks proactively.
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Implement best practices for process improvements, cost optimization and monitoring.
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Continuously evaluate and improve the Azure data platform to enhance performance and scalability.
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Collaborate with stakeholders to understand business requirements and translate them into technical solutions.
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Develop and implement a comprehensive data governance framework to ensure data quality, security, and compliance across the data applications.
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Design, evaluate impacts, perform technical design reviews, and approve technical designs as part of the design authority process.
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Establish and maintain comprehensive documentation for all data engineering processes, pipelines, and systems.
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Implement best practices for maintaining version control and traceability of documentation.
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Foster continuous learning and adoption of the latest technologies while mentoring and training the data engineering team.
Key Requirements
Essential:
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Minimum 6 years’ experience in Data Engineering, Data Architecture & Governance frameworks.
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Minimum 4 years' experience with Python, preferably PySpark.
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Experience leading small teams of Engineers.
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Excellent communication and stakeholder management abilities.
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Strong expertise in Azure: ADLS, Databricks, Stream Analytics, SQL DW, Synapse, Databricks, Azure Functions, Serverless Architecture, ARM T emplates, DevOps.
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Hands-on experience with ETL/ELT processes and data warehousing.
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Solid understanding of data security and compliance standards.
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Experience with DevOps practices and tools (e.g., CI/CD pipelines, Azure DevOps).
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The ability to simplify complex technical issues for a non-technical stakeholder audience.
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Capable of understanding business needs and requirements while providing valuable, insightful recommendations.
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Skilled in delivering presentations and technical reports clearly and persuasively
