At a Glance
- Tasks: Lead data engineering projects, solve business problems, and optimise data platforms.
- Company: Dynamic alternative asset manager with a global presence and innovative tech strategy.
- Benefits: Competitive salary, discretionary bonus, hybrid work model, and comprehensive benefits.
- Other info: High autonomy, collaborative environment, and opportunities for professional growth.
- Why this job: Join a small, impactful team and drive real change in data management.
- Qualifications: Experience in data engineering, strong Python and SQL skills, and AWS familiarity.
The predicted salary is between 80000 - 100000 £ per year.
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 Next JS 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
- Mongo DB – document storage
- Monitoring / observability tools – for alerting, debugging, and production support
- Git Hub Actions – CI/CD pipelines
- Linear – project planning and task management
- Claude Code, Cursor, Codex – AI engineering tools used in daily workflow
- Next JS / Type Script – 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
- Mongo DB 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 Next JS / Type Script
- 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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Contact Details:
CommuniTech Recruitment Group Recruitment Team
