Data analytics engineer

Hybrid working one day per week in our London, Edinburgh or Bath office.

Seccl is the Octopus-owned embedded investment platform, on a mission to help more people invest, and invest well.

We’re building the infrastructure behind the next generation of investing. Our technology already powers some of the UK’s most ambitious fintechs, banks, financial advisers and wealth firms, with close to a million investors relying on Seccl-powered platforms. And we’re now expanding into Europe.

We’ve got a proven product, strong momentum and big ambitions for what comes next: helping more household-name brands launch and scale investment propositions, entering new markets and replacing outdated investment infrastructure with technology that’s faster, simpler and built for scale.

We’re proud to be part of Octopus, one of the UK’s most successful privately held investment and technology groups. That gives us the backing and long-term perspective to build something substantial, while keeping the pace and energy of a high-growth business. Seccl and Octopus are both B Corp certified and share a belief that profit and purpose should go hand in hand.

If you want to help shape the future of investing in the UK and across Europe, you’ll be in good company.

Check out the Seccl website to see what we’re building and read more about our mission to shape the future of investments.

Seccl is growing fast, and so is the opportunity to make better use of our data. Our Data Engineering team has built strong foundations for reliable, scalable data delivery, and we’re now expanding our capabilities to make that data more accessible, actionable, and valuable to our teams and clients.

As a Data Analytics Engineer, you’ll sit at the intersection of data engineering and analytics. You’ll use strong software engineering and data modelling practices to develop production-quality datasets, while working closely with stakeholders to understand how data can help solve real business problems.

You’ll also help us evolve how data moves through our platform, including opportunities to work with streaming and event-driven technologies as we move towards more timely and incremental data processing.

• Designing, building, and maintaining robust data models using SQL and DBT, transforming complex source data into clear, reusable datasets for analytics and downstream consumers

• Working with Product managers, Engineers, Operations, and client‑facing teams to understand requirements, clarify business logic, and translate problems into scalable data solutions

• Helping define and maintain consistent metrics, modelling standards, and analytical best practices across the business

• Supporting our journey towards more real‑time and incremental data processing, including working with technologies such as MongoDB change streams, Kafka, and AWS MSK

• Helping teams become more self‑sufficient with data by making datasets understandable, well documented, and easy to consume

You’ll be successful in this role if you…

• Have strong SQL and data modelling skills and are comfortable transforming large, complex datasets into reliable, reusable analytical models

• Have experience with Python and modern analytics engineering tooling such as DBT, including testing, documentation, version control, and CI/CD practices

• Are familiar with both relational and non‑relational database architecture

• Understand dimensional modelling and how to design datasets that are intuitive and effective for analytics, BI, and downstream data products

• Have experience working with cloud data platforms and services, ideally within AWS

• Ideally have experience with event‑driven or streaming data architectures, particularly Kafka/AWS MSK, MongoDB change streams, CDC,…