Data engineer

Join a top-tier wealth and advisory firm known for its robust infrastructure, cutting-edge technology, and unwavering commitment to service excellence. To design, build and optimise robust data pipelines, models and integrations that underpin trusted data and analytics. The Senior Data Engineer provides hands on technical leadership within the engineering team, ensuring solutions are performant, cost-efficient, well tested and delivered in accordance with agreed architecture, Data Governance, security and engineering standards.

• Design, build and support complex data pipelines and data models that provide trusted, performant data for reporting, analytics and other data products, in line with agreed architecture, engineering standards and priorities.
• Provide hands-on technical leadership on assigned engineering work, contributing to solution design and ensuring implementation aligns with agreed design authority.
• Design and implement automated data quality controls, validation and testing to ensure data is reliable and fit for intended use.
• Design and build robust integrations between the Data Platform and multiple internal, external and third-party platforms, including API and SFTP-based integrations.
• Optimise Data Platform workloads, pipelines and models for performance, scalability, reliability and cost efficiency.
• Investigate and resolve complex data incidents, defects and performance issues, identifying root causes and implementing sustainable fixes.
• Document technical designs, data pipelines, models, integrations, controls and operational processes to provide clear evidence of adherence to Data Governance, privacy, security and resilience standards.
• Contribute to code reviews, source control, automated testing, CI/CD and controlled deployment practices.
• Work closely with the Data Engineering Manager, Data Product Manager, Enterprise Architect and Reporting Engineer to confirm feasibility and deliver data products that meet agreed requirements and acceptance criteria.
• Mentor and support the Data Engineer, providing technical guidance, knowledge sharing, constructive review and coaching on engineering practices.
• Identify and implement opportunities to improve engineering standards, automation, observability, platform resilience and maintainability.

• Significant hands-on data engineering experience designing, building and supporting production data platforms, pipelines and data models.
• Strong hands-on Microsoft Fabric experience, including Lakehouse, Warehouse, OneLake, pipelines and notebooks.
• Advanced SQL skills, including complex querying, data transformation, optimisation and troubleshooting.
• Strong Python and PySpark skills, with experience developing and supporting production data transformation and processing workloads.
• Strong understanding of modern data engineering patterns, including ETL/ELT, medallion architecture, data modelling, orchestration and data quality controls.
• Experience integrating multiple internal and external data sources, including APIs and SFTP.
• Experience optimising cloud data workloads for performance, scalability and cost efficiency.
• Strong experience with source control, code review, automated testing and CI/CD, ideally using Git and Azure DevOps.
• Experience diagnosing and resolving complex production data, integration and platform incidents.
• Good understanding of Data Governance, privacy and security principles and how to evidence implementation of required controls in engineering solutions.
• Experience mentoring or providing technical guidance to other Data Engineers.
• Clear documentation and communication skills, with the ability to explain technical decisions and trade-offs to technical and non-technical stakeholders.
• Curious, motivated and pragmatic, with strong problem-solving skills and ownership of technical outcomes.
• Будет плюсом: Experience in wealth management, financial services or another highly regulated environment is advantageous

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