Lead Data Engineer - Python/ AWS. Asset Management. £120,000 -£140,000+ Discretionary Bonus + B[.]

Lead Data Engineer - Python/ AWS. Asset Management. £120,000 -£140,000+ 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
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
Preferred
Experience in financial services, asset management, or hedge funds
MongoDB experience
Experience with modern data tooling
Familiarity with vendor API integrations and handling messy real‑world data
Experience with data lake patterns
Exposure to or interest in learning NextJS / TypeScript
Exposure to RAG architectures, OCR, or LLM‑based document extraction
Comfortable working in a lightweight agile workflow focused on delivery
You’ll Thrive With My Client If You:
Proactively identify problems and propose solutions rather than waiting for requirements
Are comfortable owning systems and projects end‑to‑end in a small team
Can context‑switch between building new features and keeping production stable
Prefer simple, pragmatic solutions over over‑engineered abstractions
Communicate clearly with non‑technical stakeholders
Enjoy working with a high degree of autonomy
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