Lead Data Engineer

M&G; City of Westminster; Hybrid; GBP 90,000 - 130,000; Full time

Job summary

M&G is modernising how data is sourced, engineered and consumed to support investments and AI use cases. We seek a Lead Data Engineer to design and deliver trusted data products on a Snowflake-centric platform, leading teams in London and India while partnering with Data Product, Analytics and AI domains.

You will shape data engineering standards, ensure production readiness, and drive governance, security, and observability across pipelines and data products in a dynamic Asset Management

Qualifications

• Extensive data engineering experience with leadership in Asset Management or Financial Services.
• Hands-on pipeline design and optimization on Snowflake in asset management.
• Knowledge of medallion and lakehouse architectures, ELT, and dimensional data modeling.
• Experience delivering end-to-end data products, including semantic layers for analytics/AI.
• Experience embedding data catalog, quality, lineage, observability into delivery.
• Understanding of cloud security, access management, privacy, and regulatory controls.
• Ability to collaborate across data and technology functions, manage dependencies, and share ownership.

Responsibilities

• Design and build on a modern data platform.
• Lead ingestion, transformation, and data provisioning pipelines on Snowflake.
• Apply medallion architecture to move data from raw to curated to consumption-ready.
• Translate business requirements into technical designs and data models.
• Lead and mentor data engineers across UK and India.
• Build AI-ready data and use AI in engineering.
• Migrate legacy platforms to the strategic data platform with controlled cut-over.

Skills

Data engineering

Technical lead

Snowflake

Data platform architecture

Data products

Data governance

Cloud security

Offshore leadership

Data mesh

Investment data

Tools

Snowflake

Job description

We will consider flexible working arrangements for any of our roles and offer workplace adjustments to ensure you have the support you need to succeed in your role. The Opportunity: Data and AI are at the heart of how we plan to grow our Asset Management business. We are modernising how data is sourced, engineered and consumed across the firm. The goal is trusted, reusable data products that support investment decisions, client reporting, regulatory submissions and a growing range of AI use cases. As Lead Data Engineer, you will report to the Head of Data Engineering and be the technical lead for designing and building data products on our Snowflake-centric platform. You will lead data engineers across London and India, turning our architecture and engineering standards into well‑engineered, production‑ready pipelines and data products. This is a hands‑on technical leadership role. We want an engineer who still builds, sets the bar for engineering quality and can guide others through complex design decisions. You will be the bridge between our data engineering standards and day‑to‑day delivery, making sure what we build is scalable, governed and delivers real business outcomes. What You will Do: Design and build on a modern data platform

• Lead the hands‑on design and build of ingestion, transformation and data provisioning pipelines on our Snowflake-centric platform.
• Apply the medallion architecture in practice, 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, whether 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.

Engineer governed, trusted data products

• Build data quality checks, lineage, cataloguing and data observability into every pipeline and data product from the start, rather than adding them after delivery.
• 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.
• Make sure pipelines are production‑ready, with clear monitoring, alerting and runbooks, and lead root‑cause analysis and resolution of data issues.

Lead and develop data engineers

• Provide day‑to‑day technical leadership to data engineers across the UK and India, setting clear 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.

Build AI‑ready data and use AI in engineering

• Work with Data Product, Analytics and AI teams to implement semantic models, ensuring business definitions and relationships are consistently represented in the 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.

Simplify the estate and retire legacy platforms

• Lead the 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.

• 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.
• Track record of collaborating and building effective relationships with colleagues across data and wider technology function. You should be able to 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 and 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 the controlled retirement of legacy feeds while maintaining service continuity.
• Good understanding of investment data, such as instruments, portfolios, positions and performance, with deeper asset management experience a strong advantage.

Technical toolkit:

<