Analytics Engineering

Who you are

• Extensive analytics engineering background with expert SQL and data modelling skills
• Hands-on experience with dbt (or similar framework) to build well-structured, tested, and maintainable data models
• Proficiency with Looker or a comparable BI tool
• Track record of managing, supporting, and developing analytics engineers
• Strong project management capabilities, including prioritising incoming work and delivering cross-functional data initiatives
• Excellent communication and documentation abilities
• Solid understanding of data governance and risk management
• Experience working with fraud, AML or financial crime data
• Experience in a regulated financial services environment
• Experience with cloud data warehouses and CI/CD
• Experience with Git and peer-review workflows
• If you're excited about working with us, but aren’t sure if you're 100% there yet, get in touch anyway

What the job involves

• Our Data teams are aligned to divisions covering the following Banking Services & Products, Customer Identity & Financial Crime and Data & ML Engineering
• Our Data teams are excited about delivering meaningful and impactful insights to both the business and more importantly our customers
• We are looking for talented engineers at all levels to join the team
• We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling
• People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good
• Manage and develop a team of analytics engineers
• Work closely with stakeholders to understand and prioritise key business needs
• Own and improve a large analytics estate serving many different business functions
• Lead and deliver multiple workstreams end-to-end
• Ensure quarterly priorities are delivered alongside standing work and ad hoc requests
• Maintain Fraud & AML-related regular reporting
• Support data science and ML model development and monitoring

The application 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 - 45 mins with one of the team
• Stage 2 - Take-home challenge
• Stage 3 - 60 mins technical interview with two team members
• Stage 4 - 45 min final with an two executives

Benefits

• Time off: 25 days holiday, plus your birthday as an extra freebie. You can also opt out of bank holidays and take them when works for you!
• Health insurance: Private health insurance with Vitality Health, one of the UK's leading private medical insurers
• Pension scheme
• Paid volunteering leave: We encourage all our employees to give back. You can take up to 16 hours paid leave a year, specifically to help causes meaningful to you
• Gym & cycle to work schemes: We offer discounted gym memberships and cycle to work schemes through salary sacrifice
• Perkbox: For a wide range of retail, entertainment and leisure discounts (as well as cash back) at a huge variety of businesses