Lead Data Engineer
Seven Investment Management
On-site
London, United Kingdom
Data Engineer
Purpose
Lead the design, development, and contribute to the architectural governance of data solutions across 7IM. This role combines hands-on technical leadership with strategic architectural oversight, ensuring that technology initiatives align with business goals and deliver robust, scalable, and secure solutions. You will guide both development and architecture teams, drive modernisation, and champion technical excellence.
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Responsibilities
ā¢ Lead, mentor, and motivate development teams to deliver high-quality software and data solutions.
ā¢ Contribute to the evolutionary architecture and roadmap, ensuring alignment with business strategy and objectives.
ā¢ Design, develop, test and release robust, scalable software solutions using modern technologies and best practices.
ā¢ Develop and maintain enterprise-wide data architecture models, processes and documentation.
ā¢ Ensure technical excellence, adherence to standards and minimisation of technical debt.
ā¢ Oversee the governance of technology architecture, creating meaningful metrics and KPIs.
ā¢ Collaborate with business stakeholders and technical teams to analyse needs, propose solutions and ensure alignment.
ā¢ Drive initiatives to modernise technology, tools and development processes.
ā¢ Peer review code, documentation, and architectural artefacts for accuracy, maintainability and supportability.
ā¢ Provide expert third-line support and guidance to application support teams.
ā¢ Foster innovation, identify opportunities for technical efficiencies and communicate best practices.
ā¢ Ensure compliance with regulatory standards and internal policies.
ā¢ Other duties as reasonably required by line management and 7IM.
ā¢ Contribute to the evolutionary architecture and roadmap, ensuring alignment with business strategy and objectives.
ā¢ Design, develop, test and release robust, scalable software solutions using modern technologies and best practices.
ā¢ Develop and maintain enterprise-wide data architecture models, processes and documentation.
ā¢ Ensure technical excellence, adherence to standards and minimisation of technical debt.
ā¢ Oversee the governance of technology architecture, creating meaningful metrics and KPIs.
ā¢ Collaborate with business stakeholders and technical teams to analyse needs, propose solutions and ensure alignment.
ā¢ Drive initiatives to modernise technology, tools and development processes.
ā¢ Peer review code, documentation, and architectural artefacts for accuracy, maintainability and supportability.
ā¢ Provide expert third-line support and guidance to application support teams.
ā¢ Foster innovation, identify opportunities for technical efficiencies and communicate best practices.
ā¢ Ensure compliance with regulatory standards and internal policies.
ā¢ Other duties as reasonably required by line management and 7IM.
About You
Qualifications
ā¢ Relevant degree or equivalent experience.
ā¢ Azure DP-203 (or equivalent)Ā
ā¢ Certification in Data Governance and Stewardship Professional (DGSP) or similar (desirable).
ā¢ Evidence of business experience or formal business qualifications (desirable).
ā¢ Azure DP-203 (or equivalent)Ā
ā¢ Certification in Data Governance and Stewardship Professional (DGSP) or similar (desirable).
ā¢ Evidence of business experience or formal business qualifications (desirable).
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Experience
ā¢ Proven experience in technical leadership roles (e.g., Lead Developer, Senior Data Engineer, Head of Data) within regulated environments.
Knowledge of the following is required:
o Modern Data platform concepts; Data Lake, Lakehouse, Data Warehouse, Data Vault
o Azure Data Technologies; Azure Data Lake Storage, Azure Data Factory, Azure Databricks, MS Fabric
o ETL / ELT processes and designing, building and testing data pipelines
o Building data transformations using python / pyspark
o Azure Cloud Version control and CI/CD tools, specifically Azure DevOps Service
o Analytics and MI products including MS Power BI
o Data catalog & governance using MS Purview
Knowledge of the following would be desirable:Ā
o Microsoft server-based data products (SQL Server, Analysis Services, Integration Services and Reporting Services)Ā
o Enterprise Architecture tools (e.g. LeanIX, Ardoq), Frameworks (TOGAF) and core artefacts (Capability Models, Technical Reference Models, Data Flow Diagrams
o Experience developing and implementing technology roadmaps and target state architectures.
o Experience integrating bespoke software, commercial off-the-shelf packages and third-party services.
o Demonstrable experience of migrating on-premises workloads to cloud-native services
o Excellent analytical, problem-solving and communication skills.
o Strong stakeholder management and influencing abilities at all levels.
o Ability to work efficiently under pressure and lead teams in adverse situations.
o Commitment to continuous learning and keeping skills current.
o Modern Data platform concepts; Data Lake, Lakehouse, Data Warehouse, Data Vault
o Azure Data Technologies; Azure Data Lake Storage, Azure Data Factory, Azure Databricks, MS Fabric
o ETL / ELT processes and designing, building and testing data pipelines
o Building data transformations using python / pyspark
o Azure Cloud Version control and CI/CD tools, specifically Azure DevOps Service
o Analytics and MI products including MS Power BI
o Data catalog & governance using MS Purview
Knowledge of the following would be desirable:Ā
o Microsoft server-based data products (SQL Server, Analysis Services, Integration Services and Reporting Services)Ā
o Enterprise Architecture tools (e.g. LeanIX, Ardoq), Frameworks (TOGAF) and core artefacts (Capability Models, Technical Reference Models, Data Flow Diagrams
o Experience developing and implementing technology roadmaps and target state architectures.
o Experience integrating bespoke software, commercial off-the-shelf packages and third-party services.
o Demonstrable experience of migrating on-premises workloads to cloud-native services
o Excellent analytical, problem-solving and communication skills.
o Strong stakeholder management and influencing abilities at all levels.
o Ability to work efficiently under pressure and lead teams in adverse situations.
o Commitment to continuous learning and keeping skills current.
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Skills
ā¢ Must be able to provide effective leadership within the data space, particularly when navigating ambiguity.Ā
ā¢ Must be comfortable making decisions and able to effectively execute the plan in a fast-paced environment.Ā
ā¢ Excellent verbal and written communication with a proven track record of stakeholder engagement and influencing both business and technical stakeholders
ā¢ Ability to communicate between the technical and non-technical - interpreting the needs of technical and business stakeholders, communicating how activities meet strategic goals and client needs.
ā¢ Ability to analyse data to drive efficiency and optimisation, design processes and tools to monitor production systems and data accuracy.
ā¢ Ability to produce, compare, and align different data models across multiple subject areas, reverse-engineering data models from a live system where required.
ā¢ Excellent analytical and numerical skills are essential, enabling easy interpretation and analysis of large volumes of data
ā¢ Excellent problem solving and data modelling skills (logical, physical, semantic and integration models)
ā¢ Must be comfortable making decisions and able to effectively execute the plan in a fast-paced environment.Ā
ā¢ Excellent verbal and written communication with a proven track record of stakeholder engagement and influencing both business and technical stakeholders
ā¢ Ability to communicate between the technical and non-technical - interpreting the needs of technical and business stakeholders, communicating how activities meet strategic goals and client needs.
ā¢ Ability to analyse data to drive efficiency and optimisation, design processes and tools to monitor production systems and data accuracy.
ā¢ Ability to produce, compare, and align different data models across multiple subject areas, reverse-engineering data models from a live system where required.
ā¢ Excellent analytical and numerical skills are essential, enabling easy interpretation and analysis of large volumes of data
ā¢ Excellent problem solving and data modelling skills (logical, physical, semantic and integration models)
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Other relevant information
ā¢ Experience of wealth management (including operational knowledge) would be advantageous
ā¢ Prior experience working in Financial Services preferred, thorough understanding of data security, data privacy, GDPR required
ā¢ Certification in TOGAF or equivalent structured architecture framework (desirable).
ā¢ Prior experience working in Financial Services preferred, thorough understanding of data security, data privacy, GDPR required
ā¢ Certification in TOGAF or equivalent structured architecture framework (desirable).