Lead Data Engineer – Wealth Management Platform
Location: London | Hybrid, 3 days onsite mandatory
Start: Immediate
Engagement: Permanent / FTC / Contract Inside IR35
Business Area: Wealth Management Platform
Role Overview
We are looking for an experienced and hands-on Lead Data Engineer to play a key technical role in a large-scale Wealth Management replatforming programme.
This is not a pure architecture role. The successful candidate will be expected to remain close to the code, lead engineering by example, and take ownership of building scalable data pipelines, integrations and cloud-based data solutions.
You will work closely with engineering teams, product stakeholders and platform teams to deliver a modern data ecosystem leveraging Snowflake, Python and AWS, while introducing AI-first engineering and automation practices.
Key Responsibilities
Hands-on Data Engineering
- Design, build and optimise scalable data pipelines and data processing solutions.
- Develop production-grade solutions using Python, SQL and Snowflake.
- Build robust ETL/ELT pipelines for high-volume enterprise data.
- Work hands-on with Snowflake, including data modelling, performance optimisation and scalable data solutions.
- Develop data integrations using APIs, event-driven patterns and cloud-native services.
- Design and implement reliable batch and real-time data processing solutions.
- Apply strong engineering practices across testing, CI/CD, observability, security and automation.
Technical Leadership
Act as the Lead Data Engineer for distributed engineering teams.
- Provide hands-on technical direction, code reviews and engineering guidance.
- Define reusable engineering patterns, coding standards and best practices.
- Troubleshoot complex engineering, integration and data-quality issues.
- Mentor engineers across UK, nearshore and offshore delivery teams.
- Work closely with architects while retaining direct ownership of engineering delivery.
Cloud & Data Platform Engineering
- Build cloud-native data solutions primarily using AWS and Snowflake.
- Integrate data across enterprise platforms including Salesforce, Temenos and Backbase.
- Implement scalable API and event-driven integration patterns.
- Ensure data solutions are secure, resilient, observable and performant.
AI-First Engineering
- Apply Generative AI and Agentic AI to accelerate data engineering and software delivery.
- Identify opportunities to automate development, testing, data operations and monitoring.
- Support development of data foundations required for AI/ML and GenAI use cases.
- Champion AI-assisted engineering practices across the development lifecycle.
Required Skills & Experience
- 10+ years of software/data engineering experience, with strong recent experience in senior or lead data engineering roles.
- Strong hands-on Python and SQL development experience.
- Deep hands-on experience with Snowflake.
- Strong experience designing and implementing ETL/ELT and enterprise data pipelines.
- Strong experience with AWS cloud data services and cloud-native engineering.
- Experience with API-based integrations and event-driven architectures.
- Strong understanding of data modelling, data quality, performance optimisation and data governance.
- Experience with CI/CD, automated testing and modern engineering practices.
- Ability to perform code reviews, troubleshoot production issues and guide engineers technically.
- Experience leading distributed engineering teams while remaining hands-on technically.
- Strong stakeholder communication skills.
Desirable
- Experience with Salesforce, Temenos and/or Backbase integrations.
- Exposure to Generative AI, Agentic AI or AI-enabled data platforms.
- Experience delivering large-scale platform modernisation or replatforming programmes.
- Wealth Management, Asset Management or broader Banking/Financial Services experience is preferred but not mandatory.
What We’re Looking For
We are particularly interested in candidates who are:
- Lead Data Engineers rather than pure Solution/Enterprise Architects
- Still actively hands-on with Python, SQL, Snowflake and AWS
- Comfortable owning data pipelines and integrations from design through production
- Able to lead engineers through coding, reviews, troubleshooting and technical mentoring
- Experienced in complex enterprise transformation environments
- Interested in applying GenAI and Agentic AI to modern data engineering
Interested? Apply now for an immediate discussion with our Talent Team.
#UST
AWS, Cloud Data Warehousing, Cloud Infrastructure, Cloud-Native Development, Generative AI, Machine Learning, Python, Data Engineering, Digital Transformation, Agentic AI, Event-Driven Architecture
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