Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Data Engineer - Engine by Starling

Starling Bank
London
1 month ago
Create job alert

Description

At Engine by Starling, we are on a mission to find and work with leading banks all around the world who have the ambition to build rapid growth businesses, on our technology.

Engine is Starling's software-as-a-service (SaaS) business, the technology that was built to power Starling Bank, and two years ago we split out as a separate business.

Starling Bank has seen exceptional growth and success, and a large part of that is down to the fact that we have built our own modern technology from the ground up. This SaaS technology platform is now available to banks and financial institutions all around the world, enabling them to benefit from the innovative digital features, and efficient back-office processes that has helped achieve Starling's success.

We draw upon our experience as knowledgeable bankers, and best in class technologists to become the chosen option for these banks, and preferred partners for leading consultancies.

As a company, everyone is expected to roll up their sleeves to help deliver great outcomes for our clients. We are an engineering led company and we're looking for someone who will be excited by the potential for Engine's technology to transform banking in different markets around the world.

Hybrid Working

We have a Hybrid approach to working here at Engine - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person.

About the Role

As Engine is Starling's SaaS offering we hold all of the data that is needed to run our client banks. We need to model, extract, join, format and ultimately securely share data with our clients so they can get insights into their business, build regulatory reports and run marketing campaigns.

We're already sharing millions of rows of data with our clients everyday and this is set to grow over the coming years. We're investing in our internal and external reporting tooling so we can give our clients better insights, faster and support internal operations of Engine.

As a Data Engineer you'll be at the heart of our reporting tooling, adding new data features and improving how we expose new entities to our clients and operations teams. You'll also be helping to build tooling so we can get better visibility into data lineage, data quality and how accurate our documentation is. You'll also be assisting our platform engineers to improve modelling of new features in a way that helps clients to use the data later.

Engine Engineers are excited about helping us deliver new features, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech .

Day in the Life of a Software Engineer

What you'll get to do Shape the future of data for Engine, including approaches, tooling and architecture.
Develop data as a core product offering for Engine both internally and for our clients, working with and responding to client feedback and market analysis.
Work across the boundary of software engineering and core data platform challenges.
Understand, build and develop data integration and warehousing solutions.
Deliver exceptional data solutions promoting a self service culture through trusted pipelines, quality checks, clear documentation, lineage, entity relationships and governance.
Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, etc.
Coach and mentor software engineers in the ways of data engineering across the organisation.
Obtain a wide and varied understanding of how our internal teams and client banks operate.
Work with cloud-based infrastructure (AWS, GCP) for hosting data solutions and applications.
Collaborate with clients, solution architects and other engineers to help meet the client goals.



Candidate profile:
Requirements Proven experience in development and maintenance of a cloud-based data warehouse.
Strong experience with SQL and relational databases (preferably postgres); working with Change Data Capture is a bonus.
Data modelling knowledge, breaking down backend logic to understand and form a holistic data model (ie 3NF, star schema, Data Vault).
Strong experience with Python, TypeScript or Java (a significant amount of work will be in Java - it is not expected for you to know it today but to learn from the team as it makes up a large part of the stack).
Good knowledge of Data Engineering tooling such as dbt or Spark. CDC tools like Debezium are a bonus.
Build data systems with a software and infrastructure engineer mindset, including tested, scalable, resilient, fault tolerant, observable and "as code" practices.
Good understanding of DevOps practices, Infrastructure as Code & Continuous Integration / Continuous Deployment.

Desirable Experience extracting, loading and transforming large data sets (>100GBs).
Experience with schema evolution tools such as flyway or liquibase.
Experience with AWS (S3, IAM, RDS).
Translate internal data user needs into building BI Dashboards to answer their key business questions.
Data capabilities outside of engineering (e.g. data catalogue, data modelling, data lineage, data governance, data visualisation/reporting and compliance).
Experience with data quality tooling (e.g. Great Expectations).
Experience working cross-functionally with technologists from other specialties, and non-technical stakeholders across the business.

Interview process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team: Initial interview with our Staff Data Engineer - ~45 minutes
Take home technical test to be discussed in the next interview
Technical interview with some Engineers - ~1.5 hours
Final interview with our CTO / deputy CTO ~45 minutes

Benefits 33 days holiday (including public holidays, which you can take when it works best for you)
An extra day's holiday for your birthday
Annual leave is increased with length of service, and you can choose to buy or sell up to five extra days off
16 hours paid volunteering time a year
Salary sacrifice, company enhanced pension scheme
Life insurance at 4x your salary & group income protection
Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
Generous family-friendly policies
Incentives refer a friend scheme
Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.