Analytics Engineer, QuantSpark

• Prior experience in a Data/Analytics Engineering role, ideally working alongside Analytics or Software Engineering teams
• Advanced coding skills in Python with experience with Numpy/Pandas
• Strong version control skills, with experience collaborating on large codebases and managing code across different environments
• Strong data modelling experience, with a knowledge of best practice when designing schemas
• Experience building ETL/ELT pipelines with tools such as Airflow and dbt
• Datawarehousing experience (e.g. Redshift, Snowflake)
• Some Cloud experience, ideally within AWS (S3, EC2, Lambda, etc.)
• Excellent consulting, communication, and interpersonal skills, with the ability to collaborate effectively with internal and external teams at all levels
• Good level of business acumen and an ability to deliver commercial value for clients

Desirable

• You will be joining the Analytics Engineering Team, that sits at the interface between our Software Engineering and Analytics Consulting teams, and, in general, tries to blend skills from across these disciplines
• Members of the team serve a pivotal role in our cross-functional delivery teams, assisting with the design and creation of complex analytical features, whilst also helping to facilitate effective communication across the team
• As an Analytics Engineer you’ll be responsible for working with the team to develop and maintain data pipelines, data warehouses, and data models for analytical purposes while working as an effective member of a collaborative team
• In this role, you will utilise strong communication skills to work cross functionally to deliver commercial value to clients by translating data insights into actionable solutions
• Utilise your Data Engineering expertise to design and implement scalable data pipelines, using tools such as Airflow and dbt
• Maintain existing solutions by resolving any issues which are detected and perform root cause analysis to continually improve the stability of our data platforms
• Gather requirements from stakeholders to design performant, logical data models which serve high-quality data to dashboards and business users
• Produce clear documentation for all the work you do, ensuring that all decisions, assumptions, and limitations are logged
• Work with product managers to scope out the enhancement of existing features and development of new ones
• Maintain and optimise the backend architecture of our existing Flask/Django-based web applications
• Work alongside other Analytics Engineers to deliver improvements to our ways of working e.g. adopting new tools, creating reusable packages of code, etc

• Video Call with our internal recruiter
• Technical Assessment to be completed at home
• Technical Interview in person with our Analytics Engineering team
• Final interview with our COO and Head of Engineering