Data Engineer - Data Pipelines

Starling Bank
London
5 days ago
Create job alert

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that youre located within a commutable distance of one of our offices so that were able to interact and collaborate in person.

Responsibilities:

  • Understand, build and develop batch/file based data pipelines in AWS and GCP, using file transfers, REST APIs etc.
  • Build tools to monitor, report and control data pipelines.
  • Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, etc.
  • Work with cloud-based infrastructure (GCP) for ingesting data into our warehouse.
  • Collaborate with other full stack developers and data engineers to help meet the business goals.

The main part of our Tech Stack is listed below, we dont ask that you have experience in all of this, but if you do, thats great!

  • Java, which makes up the majority of our backend codebase.
  • AWS & GCP - were cloud-native.
  • Microservice based architecture.
  • Kubernetes (EKS).
  • TeamCity for CI / CD (lots of teams are releasing code 15-20 times per day!).
  • Terraform and Grafana.

In addition to this core stack, this role is focused on the engineering required to maintain and warehouse a wide variety of data sources used across the bank. The technology we use is cloud based, primarily GCP. Experience with some or all of the services below would put you at the top of our list:

  • Google Cloud Storage.
  • Google Data Transfer Service.
  • Google Dataflow (Apache Beam).
  • Google PubSub.
  • Google CloudRun.
  • BigQuery or any RDBMS.
  • Python.
  • Debezium/Kafka.
  • dbt (Data Build tool).

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:

  • Stage 1 - 30 mins with one of the team.
  • Stage 2 - 60 mins technical interview with two team members.
  • Stage 3 - 45 min final with an executive and a member of the people team.

Benefits:

  • 25 days holiday (plus take your public holiday allowance whenever 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.
  • 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.

About Us

You may be put off applying for a role because you dont tick every box. Forget that! While we can’t accommodate every flexible working request, were always open to discussion. So, if youre excited about working with us, but aren’t sure if youre 100% there yet, get in touch anyway. We’re on a mission to radically reshape banking – and that starts with our brilliant team. Whatever came before, we’re proud to bring together people of all backgrounds and experiences who love working together to solve problems.

Starling Bank is an equal opportunity employer, and we’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Starling Bank are considered without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, physical or mental disability, military or veteran status, or any other characteristic protected by applicable law.

J-18808-Ljbffr

Related Jobs

View all jobs

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Data Engineer

Get the latest insights and jobs direct. Sign up for our newsletter.

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 Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

Machine Learning Jobs in the Public Sector: Opportunities Across GDS, NHS, MOD, and More

Machine learning (ML) has rapidly moved from academic research labs to the heart of industrial and governmental operations. Its ability to uncover patterns, predict outcomes, and automate complex tasks has revolutionised industries ranging from finance to retail. Now, the public sector—encompassing government departments, healthcare systems, and defence agencies—has become an increasingly fertile ground for machine learning jobs. Why? Because government bodies oversee vast datasets, manage critical services for millions of citizens, and must operate efficiently under tight resource constraints. From using ML algorithms to improve patient outcomes in the NHS, to enhancing cybersecurity within the Ministry of Defence (MOD), there’s a growing demand for skilled ML professionals in UK public sector roles. If you’re passionate about harnessing data-driven insights to solve large-scale problems and contribute to societal well-being, machine learning jobs in the public sector offer an unparalleled blend of challenge and impact. In this article, we’ll explore the key reasons behind the public sector’s investment in ML, highlight the leading organisations, outline common job roles, and provide practical guidance on securing a machine learning position that helps shape the future of government services.