At a Glance
- Tasks: Design and implement a cloud-native data warehouse and machine-learning platform.
- Company: Join Starling, the UK's leading digital bank focused on innovation and transparency.
- Benefits: Enjoy 25 days holiday, private medical insurance, and flexible working options.
- Other info: Collaborative culture with opportunities for personal growth and community involvement.
- Why this job: Make a real impact in banking by leveraging cutting-edge technology and data engineering.
- Qualifications: Expertise in Kubernetes, Python or Java, and experience with cloud providers like AWS or GCP.
The predicted salary is between 63000 - 77000 £ per year.
Starling is the UK’s first and leading digital bank dedicated to fixing banking.
With a focus on fast technology, fair service and honest values, we aim to make banking simpler, quicker and more transparent for everyone.
Hybrid Working
We ask that technology staff attend the office at least one day per week and that candidates are based within commuting distance of one of our London, Southampton, Cardiff or Manchester offices.
Our Data Environment
Our Data teams support Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering.
They deliver actionable insights to the business and the customer, leveraging cloud-native platforms and modern data engineering practices.
- What You’ll Be Doing
- Building for Scale – lead the design and implementation of a cloud‑native data warehouse and machine‑learning platform that is robust, secure and scalable.
- Mastering Orchestration – dive deep into Kubernetes, using Operators and Helm to automate complex data workflows and platform management.
- Bridging the Clouds – improve existing tooling and enable seamless integrations between our AWS and GCP environments.
- Defining Our State – use Terraform to manage and document our entire data infrastructure as code, ensuring reproducibility and transparency across the stack.
Requirements
- Solid expertise with Kubernetes, Operators and Helm for managing application lifecycles.
- Proficiency in Python or Java, and a passion for writing clean, efficient code to solve infrastructure challenges.
- Comfortable working with at least one major cloud provider (AWS or GCP) and an understanding of how to optimally use their managed services.
- Experience refining and deploying green‑field, Kubernetes‑native open‑source projects.
- Bonus Points If You Have
- Experience with SQL‑based transformation workflows (e. g., dbt within Big Query).
- Familiarity with streaming and ingestion technologies such as Kafka or Debezium.
- A background in Linux administration or data‑management best practices.
- Interview Process
Interviewing is a two‑way conversation. It typically proceeds through the following stages:
- Stage 1 – 30‑minute chat with a team member.
- Stage 2 – Take‑home challenge.
- Stage 3 – 60‑minute technical interview with two team members.
- Stage 4 – 45‑minute final interview with two data executives.
Benefits
- 25 days holiday (plus public holidays); an extra day off for your birthday.
- Annual leave that increases with length of service and the option to buy or sell up to five extra days.
- 16 hours paid volunteering time per year.
- Salary sacrifice, company‑enhanced pension scheme.
- Life insurance at 4× your salary and group income protection.
- Private medical insurance (including mental‑health support and cancer care); partner discounts with Waitrose, Mr & Mrs Smith and Peloton.
- Generous family‑friendly policies.
- Perkbox membership for retail discounts, wellness platform, and weekly perks.
- Access to initiatives such as Cycle to Work, salary‑sacrificed gym partnerships and electric‑vehicle leasing.
About Us
We are open to candidates who may not tick every box and welcome people of all backgrounds and experiences.
Our culture is fast, collaborative and focused on innovation, with a flat structure that empowers you to make decisions and build impactful products.
Starling Bank is an equal‑opportunity employer.
We consider all individuals for employment without regard to race, religion, national origin, age, sex, gender, gender identity, gender expression, sexual orientation, marital status, medical condition, ancestry, disability or veteran status.
Information you provide is processed in accordance with our Privacy Notice and used for recruiting purposes.
#J-18808-Ljbffr
Data Platform Engineer employer: Starling
Starling Bank is an exceptional employer that prioritises employee well-being and professional growth, offering a vibrant work culture in Manchester. With a commitment to flexible working, comprehensive benefits, and a focus on innovation, employees are empowered to make a meaningful impact in the banking industry while enjoying a supportive and inclusive environment. Join us to be part of a forward-thinking team dedicated to doing the right thing and shaping the future of banking.
StudySmarter Expert Advice🤫
We think this is how you could land Data Platform Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Starling!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Platform Engineer at Starling.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Starling.
✨Apply Directly through Our Website
When you find a suitable opening like Data Platform Engineer at Starling, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Platform Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Starling, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Starling. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Starling
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Starling!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.