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- Tasks: Shape the future of data by developing core products and trusted data pipelines.
- Company: Engine by Starling powers banks globally with innovative technology and a commitment to excellence.
- Benefits: Enjoy 33 days holiday, birthday perks, volunteering days, and private health insurance.
- Why this job: Join a passionate team transforming banking with cutting-edge technology and diverse collaboration.
- Qualifications: Proven experience with cloud data warehouses, strong SQL skills, and familiarity with Python or TypeScript.
- Other info: We value diversity and encourage all applicants to apply, regardless of background.
The predicted salary is between 36000 - 60000 £ per year.
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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.
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
About Us
You may be put off applying for a role because you don\’t tick every box. Forget that! While we can\’t accommodate every flexible working request, we\’re always open to discussion. So, if you\’re excited about working with us, but aren\’t sure if you\’re 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.
Engine by Starling is an equal opportunity employer, and we\’re proud of our ongoing efforts to foster diversity & inclusion in the workplace. Individuals seeking employment at Engine by Starling 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.
When you provide us with this information, you are doing so at your own consent, with full knowledge that we will process this personal data in accordance with our Privacy Notice. By submitting your application, you agree that Engine by Starling and Starling Bank will collect your personal data for recruiting and related purposes. Our Privacy Notice explains what personal information we will process, where we will process your personal information, its purposes for processing your personal information, and the rights you can exercise over our use of your personal information.
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Data Engineer - Engine by Starling employer: Starling Bank
Contact Detail:
Starling Bank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Engine by Starling
✨Tip Number 1
Familiarise yourself with Engine by Starling's technology and the specific data challenges they face. Understanding their SaaS platform and how it serves banks globally will help you articulate your insights during interviews.
✨Tip Number 2
Network with current employees or alumni who have worked at Engine by Starling. Engaging in conversations about their experiences can provide you with insider knowledge and potentially valuable referrals.
✨Tip Number 3
Prepare to discuss your experience with cloud-based data warehouses and relevant tools like dbt or Spark. Be ready to share specific examples of how you've built resilient data systems in previous roles.
✨Tip Number 4
Practice articulating your understanding of data governance, lineage, and quality. Being able to explain these concepts clearly will demonstrate your expertise and alignment with Engine's goals.
We think you need these skills to ace Data Engineer - Engine by Starling
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, particularly with cloud-based data warehouses and SQL. Emphasise any projects where you've worked with large datasets or developed data integration solutions.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for Engine by Starling's mission and how your skills align with their needs. Mention specific technologies you’ve worked with, such as Python or AWS, and how they relate to the role.
Showcase Your Technical Skills: If applicable, include links to your GitHub or portfolio showcasing projects that demonstrate your data engineering capabilities. Highlight any experience with tools like dbt, Spark, or CDC tools like Debezium.
Prepare for the Interview: Research common data engineering interview questions and be ready to discuss your past experiences. Familiarise yourself with Engine by Starling’s technology stack and think about how you can contribute to their goals.
How to prepare for a job interview at Starling Bank
✨Understand the Company and Its Technology
Before your interview, take some time to research Engine by Starling and its SaaS platform. Familiarise yourself with their technology, recent developments, and how they serve banks globally. This will help you demonstrate your enthusiasm and understanding of their mission during the conversation.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with cloud-based data warehouses, SQL, and any relevant programming languages like Python or Java. Highlight specific projects where you've built data pipelines or worked with large datasets, as this aligns closely with the role's requirements.
✨Prepare for Technical Assessments
Since the interview process includes a take-home technical test, practice common data engineering problems and scenarios. Brush up on your knowledge of data modelling techniques and tools like dbt or Spark, as these may come up in discussions.
✨Emphasise Collaboration and Mentorship
Engine values teamwork and mentorship, so be ready to share examples of how you've collaborated with both technical and non-technical teams. Discuss any experiences where you've mentored others in data engineering practices, as this will show your ability to contribute to the team's growth.
