Job Description
Senior Analytics Engineer (x3)
Contract: 6 months
Location: London
Rate: £500 per day
We are working with a public sector organisation looking for experienced Senior Analytics Engineers to join their Data Modelling and Engineering team. This team is responsible for building and maintaining data pipelines from operational services to their Analytical Platform.
As an Analytics Engineer, you will be developing dimensional models on top of these data pipelines to provide valuable, accessible data to users, including analysts, performance teams, and data scientists. Your work will help modernise and streamline processes that are currently manual, inefficient, and prone to error.
With new digital services being developed to replace legacy databases, your support will be crucial in maintaining critical data feeds to downstream systems. As many current models were created for specific reporting purposes, there is now an opportunity to step back and build a comprehensive data model that better reflects business processes and analytical needs.
We are looking for a highly collaborative, experienced Analytics Engineer with strong data modelling skills to accelerate this development.
Essential Skills:
- Excellent SQL and Jinja skills
- Proficient in dbt, including implementing best practices
- Experience in developing and testing data models aligned with business requirements
- Expertise in drafting and reviewing data documentation to ensure accuracy and completeness
- Strong background in designing and developing conceptual, logical, and physical data models
- Experience working with data users to understand data in relation to business processes.
Desirable Skills:
- Experience with Python programming
- Familiarity with cloud platforms, particularly AWS
- Experience building dashboards or data applications
- Understanding of CI/CD workflows, ideally with GitHub Actions
If this role sounds like a good fit, please send over your CV, and we’ll be in touch to schedule a call!
You'll need to happy to travel to London twice a month.