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M&G

Publicly traded savings and investments company

Lead Data Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

  • Significant experience in data engineering, including experience as a technical lead within Asset Management or Financial Services.
  • Strong hands-on experience building and optimising data pipelines and data products on Snowflake, ideally in an asset management setting.
  • Solid knowledge of modern data platform architecture, including medallion and lakehouse patterns, ELT and dimensional or domain data modelling.
  • Experience delivering data products end to end, including contributing to semantic layer implementation for analytics and AI use.
  • Practical experience embedding data catalogue, data quality, lineage and data observability tooling into engineering delivery.
  • Good understanding of cloud security, access management, data privacy and regulatory control requirements.
  • Ability to collaborate and build effective relationships across data and the wider technology function, share ownership, manage dependencies and agree joint priorities.
  • Experience leading and mentoring offshore engineering teams as an integrated part of the function through code reviews, coaching, technical direction and a one-team culture.
  • Experience working in data mesh or hub-and-spoke data operating models.
  • Experience delivering data platform migrations, including data reconciliation and controlled retirement of legacy feeds while maintaining service continuity.
  • Good understanding of investment data, such as instruments, portfolios, positions and performance.

Responsibilities

  • Lead the hands-on design and build of ingestion, transformation and data provisioning pipelines on the Snowflake-centric platform.
  • Apply the medallion architecture, promoting data from raw to curated to consumption-ready layers in line with agreed standards.
  • Translate business and data product requirements into robust technical designs, data models and delivery plans.
  • Build and evolve reusable ingestion, transformation and consumption patterns for BI, APIs, data sharing or AI.
  • Help shape data engineering standards for ELT, orchestration, data modelling, testing, DataOps, CI/CD and observability, working with the Head of Data Engineering.
  • Build data quality checks, lineage, cataloguing and data observability into every pipeline and data product from the start.
  • Implement data contracts, metadata and certification standards so each data product is discoverable, trusted and auditable.
  • Apply security and compliance by design, including role-based access control, secrets management, encryption, data classification, retention and privacy controls.
  • Ensure pipelines are production-ready with clear monitoring, alerting and runbooks, and lead root-cause analysis and resolution of data issues.
  • Provide day-to-day technical leadership to data engineers across the UK and India, setting priorities and removing blockers.
  • Lead design reviews, code reviews and pairing to raise engineering quality and consistency across the team.
  • Coach and mentor engineers, helping them grow their technical skills and shift from building individual pipelines to delivering reusable data products.
  • Work with offshore engineers as one integrated team, with shared standards, ways of working and ownership.
  • Work with Data Product, Analytics and AI teams to implement semantic models so business definitions and relationships are consistently represented in engineered data products.
  • Use AI-assisted tools across the engineering lifecycle, from code generation and testing to documentation and data quality monitoring, with appropriate human oversight.
  • Lead technical delivery of migrations from legacy data platforms and point-to-point data feeds onto the strategic platform, with data reconciliation and controlled cut-over.
  • Consolidate duplicated pipelines into reusable data products and actively reduce technical debt.
  • Design efficient pipelines and optimise compute and storage so cost efficiency is built into delivery.

Desired Qualifications

  • Databricks exposure is an advantage.
  • Deeper asset management experience is a strong advantage.

About the Company

M&G

Publicly traded savings and investments company

M&G is a savings and investments company that manages money for individuals and institutions. It offers a range of investment products, including mutual funds, where many investors pool their money to buy a fixed mix of assets chosen by the fund manager. The funds are then managed to try to grow wealth and provide long-term returns, with investors’ money divided into shares or units based on the fund’s rules. M&G differentiates itself through its long history as an asset manager, its status as an independently listed company after the demerger from Prudential, and its focus on serving the UK and European markets with a broad lineup of funds and investment strategies. Its goal is to help people save and invest for the long term by providing access to professionally managed portfolios and investment options that suit different risk tolerances and goals.

Company size
1,001-5,000
Company stage
IPO
Headquarters
London, United Kingdom
Founded
1931

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