Data Engineer, Engine by Starling

• 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

• 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
• 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
• 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

• 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