Starling Bank

Staff Data Engineer - Engine By Starling

London, UK
GCP SQL Python Spark Kubernetes Terraform Java AWS
Description

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.

Our Engineering Environment

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.

We are looking for 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 Engine. 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 Engine, to continue changing banking for good.

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

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 reporting tooling so we can give our clients better insights - and faster.

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. 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. We are also on the lookout for Database Infrastructure Engineer too.

What you’ll get to do

  • Shape the future data strategy at Engine, including approaches, tooling and architecture.
  • Develop data as a core product offering for Engine, working with and responding to client feedback and market analysis.
  • Hire, build, coach and mentor a data engineering team to implement the future of data in Engine.
  • Understand, build and develop data integration and warehousing solutions
  • Obtain a wide and varied understanding of how our client banks operate
  • Explore ways to monitor and enhance data quality and reliability
  • Identify, design, and implement internal process improvements: automating manual processes, optimising data delivery, etc.
  • 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

  • Experience building strong data engineering teams
  • Proven experience in development and maintenance of a cloud-based data warehouse
  • Experience working across multiple teams, delivering complex outcomes across multiple domains
  • Experience working cross-functionally with technologists from other specialties, and non-technical stakeholders across the business
  • Exposure to data capabilities outside of engineering (e.g. data catalogue, data modelling, data lineage, data governance, data visualisation/reporting and compliance)
  • Strong experience with SQL and relational databases
  • Experience with Python or Java-based data processing frameworks such as Beam, Dataflow, Spark etc. 
  • Good understanding of DevOps practices and Infrastructure as Code
  • Good knowledge of data engineering tooling such as; dbt, Debezium
  • Experience with data quality tooling (e.g. Great Expectations)
  • Experience supporting and working with cross-functional teams in a dynamic environment

The main part of our Tech Stack is listed below, we don't ask that you have experience in all of this, but if you do, that's great!

  • Java, which makes up the majority of our backend codebase
  • Micro-service based architecture
  • Kubernetes
  • TeamCity for CI / CD (our teams are releasing code many times per day!)
  • Terraform

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 an Engineer
  • Stage 2 - 90 mins technical interview with two team members 
  • Stage 3 - 45 min final with an executive

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