Senior Data Engineer

Our client's organisation is on a journey to become an AI-first organization.

As part of that journey, their AI and Data team builds the data infrastructure that powers financial reporting, investment decision-making, and operational workflows across the firm.

The Senior Data Engineer will take technical ownership of the data pipelines and data models behind their financial data platform. This is a hands-on senior role.

You'll make architectural decisions, work directly with finance stakeholders, and be accountable for what ships. Strong data engineering fundamentals matter as much as domain knowledge here.

The majority of the work is data engineering: designing data models, building reliable pipelines, and making sure the financial data the business depends on is accurate, well-structured, and built to last.

Responsibilities

Data modeling and architecture

Design and evolve the data models that power financial reporting across multiple fund types and investment strategies

Define how financial data is structured, named, and documented so it scales as the business grows

Build shared abstractions and reusable components that other engineers can build on top of with confidence

Know when to push back on shortcuts that'll cost the team later, and when pragmatism is the better call

Pipeline ownership

Design, build, and own production data pipelines that move and transform financial data from source systems through to reporting

Set up monitoring, alerting, and data quality checks across critical datasets

Take on-call responsibility for the pipelines you own and see incidents through to resolution

Continuously improve performance, reliability, and cost efficiency of the platform

Collaboration and technical leadership

Work directly with finance and operations teams to understand their workflows (not just their requirements) and design accordingly

Provide technical guidance and mentorship to other engineers on the team

Drive projects from problem definition through to rollout without needing heavy direction

Qualifications

Must-have experience

4+ years in data engineering or data platform roles where you owned production systems end to end, including the operational side

Strong data modeling fundamentals (relational, dimensional, or event-driven) and the ability to design schemas that serve both analytical and operational needs

Experience building and running pipelines in production: scheduling, debugging, monitoring, and being on the hook when things break

Strong SQL and comfort working with large datasets in warehouses or lakehouses

Track record of working with non-technical stakeholders to turn messy business requirements into clean data designs

You're self-directed. You find the problem, figure out the approach, and ship it.

Nice to have (not required)

Background in financial services, fintech, or any domain where data accuracy has real consequences

Experience on a platform or enablement team where you've built things other engineers depend on

Familiarity with GCP or a comparable cloud data platform

Python for pipeline logic and transformation work

How the Organisation Works

High ownership:
You'll be trusted to set direction and make pragmatic decisions on platform-level data problems

Technology-agnostic:
We choose tools that fit our problems, not the other way around. Your ability to learn and adapt is more important than any specific stack.

Collaborative and low-ego:
We value curiosity, clear communication, and bias toward action.

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