Location
London

Hours
Full Time

Salary
Competitive salary

About the Role
The Analytics Engineer is a hands-on technical role within JustPark's data team, positioned at the intersection of data engineering and analytics. You will be responsible for building and maintaining clean, well-tested data models that power reporting, BI, and business decision-making across our two-sided marketplace. Working closely with the Data Platform and BI teams, you will translate raw data into trusted, scalable assets that shape how JustPark makes decisions. This role is ideal for someone fluent in dbt and BigQuery, who enjoys owning modelling problems end-to-end and can thrive in a fast-moving product environment.

Responsibilities include building, testing, and documenting dbt models in BigQuery across staging, intermediate, and mart layers that support analytics and reporting; partnering with the BI team and Data Platform Lead to convert business questions into reusable, well-modelled data assets; collaborating with backend engineers to anticipate schema changes and resolve data quality issues at source; improving the data warehouse by reducing complexity, enhancing query performance, and managing BigQuery costs; and contributing to data governance through documentation, naming standards, discoverability, and exploring emerging AI tooling to strengthen the data platform.

Success in the first 3 months means gaining a solid understanding of the existing dbt project, data models, and key reporting areas; independently delivering well-structured, tested dbt models trusted by analysts and stakeholders; identifying meaningful improvements in the warehouse; building effective working relationships with BI, Data Platform, and backend teams; and contributing to documentation and governance to facilitate future team work.

Experience
- 4+ years of hands-on dbt Core experience in a production environment
- Proficient in SQL and knowledgeable in modern data warehouse concepts such as dimensional modelling and layered architecture
- Practical experience with cloud data warehouses, capable of writing efficient queries and improving performance
- Ability to translate business requirements into delivered data models, working from problem to shipped solution
- Understanding of transactional vs analytical systems and the impact of backend schema changes on downstream models
- Comfortable with git-based development workflows including pull requests, code reviews, and team coding standards
- Ownership of data quality in built models, proactively identifying and resolving issues
- Curiosity about AI applications in data and leveraging modern tooling and semantic layers to build intelligent data products

About you
Detail-oriented and proactive with strong collaboration skills, able to work effectively with BI teams, data platform leads, and backend engineers. You thrive in a fast-paced environment and are motivated to continuously improve data infrastructure and governance.

Qualifications
While specific formal qualifications are not listed, the role requires extensive practical experience with dbt, SQL, cloud data warehouses, and modern data engineering practices. Familiarity with AI tooling and semantic layers is a plus.

Nice-to-haves
- Experience with dbt Cloud and BigQuery scheduling, orchestration, and warehouse optimisation
- Familiarity with Tableau or supporting analysts using BI tools
- Experience building semantic layers, especially related to LLM and AI applications
- Experience with CDC pipelines or event-driven data architectures
- Python skills for data transformation or automation tasks