Analytics Engineer

G-Research

Greater London

On-site

GBP 60,000 - 80,000

Full time

14 days+

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Benefits offered by this job

Highly competitive compensation

Annual discretionary bonus

Lunch provided

30 days annual leave

9% company pension contributions

Comprehensive healthcare

Cycle-to-work scheme

Monthly company events

Job summary

G-Research is seeking an Analytics Engineer in London to develop data models and AI-assisted workflows. The role involves owning stakeholder relationships and delivering analytics engineering work to support data-driven decisions. Candidates should have strong experience in analytics engineering, data transformation using Python and SQL, and familiarity with CI/CD and AI tools. The company offers competitive compensation, comprehensive healthcare, and a supportive work environment.

Qualifications

Experience in analytics engineering, data engineering or a similar role.
Strong data transformation skills using Python and SQL.
Fluent in CI/CD, Docker/Kubernetes, and Linux.
Practical use of AI tools in your day-to-day work.
Proven track record of independently owning delivery.
Excellent interpersonal and communication skills.
An innovative mindset with a desire to improve.

Responsibilities

Own the analytics engineering relationship and roadmap.
Develop clean, tested, and reusable datasets.
Build tools and AI-embedded workflows.
Apply software engineering practices to the analytics stack.
Collaborate with data analysts and business stakeholders.

Skills

Analytics engineering

Data transformation using Python

SQL

CI/CD

Docker/Kubernetes

Version control

AI tools

Interpersonal skills

Tools

dbt core

dlt

Job description

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.

From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve. Together we’re building a world-class platform to amplify our teams’ most powerful ideas.

Every breakthrough is built on strong foundations. In our Strategy and Insights team, you’ll work across disciplines to drive the strategy, culture and structure that enable our success.

Take the next step in your career.

The role

Our Platform and Data Architecture team is part of the wider Strategy and Insights function, which is collectively responsible for providing timely insights on the firm’s health and for the development and delivery of G-Research's strategy.

Data is at the heart of what we do and we see the ability to embed data-driven insight into the fabric of daily management as a core driver of competitive advantage for the firm.

As an Analytics Engineer you will develop deep knowledge in one or more domains, own the stakeholder relationship and own the roadmap and delivery of analytics engineering work. You will build the data models, tools and AI-assisted workflows that support stakeholders in making data driven decisions with confidence.

Key responsibilities of the role include:

Owning the analytics engineering relationship and roadmap for one or more business areas, turning stakeholder priorities into a prioritised programme of work
Developing clean, tested, documented and reusable datasets that power analyst-led deep dives, stakeholder self-service and agentic data analysis
Building tools, such as python packages, and AI-embedded workflows using langgraph that help analysts and stakeholders work faster and more confidently
Applying software engineering practice to the analytics stack, including CI/CD, containerisation, Linux tooling, testing and code review, and continuously raising the bar on our technology choices

Collaborating with and supporting data analysts and business stakeholders, advocating best practice in data modelling, engineering and self-service analytics

Who are we looking for?

The ideal candidate will have the following skills and experience:

Experience in analytics engineering, data engineering or a similar role, with equal measures of technical ability and business acumen
Strong data transformation skills using python and SQL, with hands-on experience of modern code-based transformation and ingestion frameworks, such as dbt core and dlt
Fluent in a modern software engineering environment, such as CI/CD, Docker/Kubernetes, Linux, version control, with a good understanding of DataOps
Practical use of AI tools in your day-to-day work and, ideally, experience building workflows or applications that put AI to work on real problems
A proven track record of independently owning end-to-end delivery, including scoping with stakeholders, design, delivery and support
Excellent interpersonal and communication skills, with the ability to build trusted relationships with senior stakeholders and bring them along on self-service
An innovative mindset with a desire to continuously improve every aspect of how we work

Why join us?