Data Engineer - Python/ AWS. Asset Management. £110,000-£120,000 + Discretionary Bonus + Benefits. Hybrid 2 Days a week in Central London office.

Data Engineer - Python/ AWS. Asset Management. £110,000-£120,000 + Discretionary Bonus + Benefits. Hybrid 2 Days a week in Central London office.

My client is a US$5bn+ alternative asset manager operating across seven global offices: New York, BVI, London, Switzerland, Dubai, Singapore, and Hong Kong. The firm serves institutional investors and high-net-worth clients through a range of alternative investment strategies.

My clients technology strategy is built around a proprietary, cloud-native platform. The firm’s technology function is structured as a lean, high-output engineering team comprising three developers led by the firm’s COO. This structure means every engineer has significant ownership, direct impact on the platform, and close visibility to senior leadership and business stakeholders.

The Role

They are looking for a Data Engineer to join their small engineering team and help evolve their data platform alongside two other engineers.

This is not a narrowly defined “build what you’re told” role. They need someone who can identify business problems, map data architecture, and help drive solutions end-to-end. You’ll work directly with operations, research, and investment teams to understand what data they need, where bottlenecks exist, why data is delayed or missing, and how to improve the flow of data across the business.

This role is fundamentally data-engineering focused. They are looking for someone with strong data engineering fundamentals who is comfortable owning production systems, improving reliability and freshness, and working across team boundaries when needed. The role spans both operating existing production pipelines and building new capabilities, with priorities shifting based on business needs.

You should be comfortable working in a small team with high autonomy, wearing multiple hats, and moving between technical investigation, stakeholder conversations, and hands-on delivery.

What You’ll Do

Solve business problems with data — work with ops, research, and investment teams to identify pain points and deliver practical solutions, not just tickets

Improve the data platform end-to-end — ingestion, transformation, storage, serving, observability, and reliability

Optimise data freshness and reliability — reduce latency, eliminate stale data, and improve alerting so failures are not silent

Map and improve data architecture — identify inefficiencies, reduce unnecessary handoffs, and streamline how data flows from vendors to consumers

Operate and maintain production data pipelines ingesting from financial data vendors

Build and extend new vendor integrations, data products, and pipeline features

Manage infrastructure on AWS using Terraform

Build AI capabilities including RAG pipelines and OCR-based document extraction to unlock unstructured data sources

Collaborate with the wider engineering team, including on systems that interact with our client-facing NextJS application

Plan and prioritise work in collaboration with technical and non-technical stakeholders

Tools & Technologies

Python — primary language for ETL, API clients, data validation, and pipeline development

SQL — analytical and transactional queries, transformations, and data investigation

AWS — cloud infrastructure and managed services

Terraform — infrastructure-as-code

MongoDB — document storage

Monitoring / observability tools — for alerting, debugging, and production support

GitHub Actions — CI/CD pipelines

Linear — project planning and task management

Claude Code, Cursor, Codex — AI engineering tools used in daily workflow

NextJS / TypeScript — exposure helpful, but this is not a full-stack role

What they are Looking For:

Required:

• Experience as a Data Engineer or in a similar role
• Proven ability to identify business problems and deliver end-to-end data solutions, not just implement specifications
• Strong Python and SQL skills
• Experience with AWS services
• Infrastructure-as-code experience
• Comfort with production operations — monitoring, incident response, and debugging distributed systems Strong stakeholder communication skills — you’ll work directly with non-technical teams across the business
• Comfortable using modern AI engineering tools in day-to-day work

Preferred:

• Experience in financial services, asset management, or hedge funds
• MongoDB experience
• Experience with modern da…