At a Glance
- Tasks: Build and maintain data models that drive analytics and reporting for JustPark.
- Company: Join JustPark, the leading platform simplifying parking experiences for drivers and partners.
- Benefits: Enjoy 25+ days holiday, free lunches, private medical insurance, and more!
- Other info: Collaborative culture with great career growth and fun team activities.
- Why this job: Make a real impact by transforming raw data into trusted insights in a fast-paced environment.
- Qualifications: 4+ years of dbt experience, SQL proficiency, and a passion for data quality.
The predicted salary is between 50000 - 60000 £ per year.
About Just Park
Just Park is the premier partner offering both B2B solutions for destinations and B2C services for drivers, giving us the best of both worlds.
We simplify the entire parking experience.
From venues and councils to private driveways, our platform makes it simple for drivers to find, book, and pay for parking, while empowering our operating partners to deliver exceptional parking experiences.
About The Role
The Analytics Engineer is a hands‑on technical role within Just Park's data team, positioned at the intersection of data engineering and analytics.
You will build and maintain 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 Just Park makes decisions.
This role is ideal for someone fluent in dbt and Big Query, who enjoys owning modelling challenges end‑to‑end and can hit the ground running in a fast‑moving product environment.
Responsibilities
- Build, test, and document dbt models in Big Query across the staging, intermediate, and mart layers that power analytics and reporting across the business.
- Partner with the BI team and Data Platform Lead to turn business questions into reusable, well‑modelled data assets.
- Work with backend engineers to stay ahead of schema changes and resolve data quality issues at source rather than patching them downstream.
- Improve the warehouse over time — reducing complexity, improving query performance, and keeping Big Query costs in check.
- Contribute to data governance: documentation, naming standards, discoverability, and exploring how emerging AI tooling can strengthen the data platform.
- Success in the First 3 Months
- Demonstrate a solid understanding of the existing dbt project, data models, and key reporting areas, and work independently on modelling tasks with minimal direction.
- Ship well‑structured, tested dbt models that analysts and stakeholders can trust and use, and identify at least one area of the warehouse to meaningfully improve.
- Build effective working relationships with the BI team, Data Platform Lead, and backend engineers, staying ahead of schema changes rather than reacting to them.
- Document and governance contributions are in place, making it easier for the team to build on the work moving forward.
Requirements
- Must‑haves
- 4+ years of hands‑on dbt Core experience in a production environment.
- Proficient in SQL and comfortable with modern data warehouse concepts such as dimensional modelling and layered architecture.
- Practical cloud data warehouse experience, with the ability to write efficient queries and a solid understanding of how to improve performance.
- Translates business requirements into delivery, comfortable working from a business problem through to a shipped model.
- Understands the distinction between transactional and analytical systems, and how backend schema changes can affect downstream data models.
- Comfortable working in a git‑based development workflow, including pull requests, code reviews, and contributing to team coding standards.
- Takes ownership of data quality in the models they build, proactively identifying and resolving issues rather than treating it as someone else’s problem.
- Curiosity about AI applications in data, including how modern tooling and semantic layers can be leveraged to build more intelligent data products.
- Nice‑to‑haves
- Experience with dbt Cloud and Big Query, including scheduling, orchestration, and warehouse optimisation.
- Familiarity with Tableau or supporting analysts who use BI tools.
- Experience building semantic layers, ideally with an understanding of how they support LLM and AI applications.
- Experience with CDC pipelines or event‑driven data architectures.
- Python for data transformation or automation tasks.
Benefits
- Recharge your batteries
- Generous holiday policy: 25 days + bank holidays + managers can grant up to 5 extra days for high performance (total of 38 days a year).
- Free lunch on all office days via Feedr with daily meal choice.
- Free snacks & drinks on all office days.
- Investment in you and your wellbeing
- Private Medical Insurance with Vitality.
- Life assurance through Yu Life.
- £25 credit for eye tests per year.
- Free O2 concert tickets through our partnership with the O2.
- Simplifying journeys so you can breathe easier
- £50 parking credit per month via Just Park.
- Cycle‑to‑work salary sacrifice scheme.
- EV salary sacrifice car scheme via Octopus Energy.
- We look out for your family
- Enhanced parental leave with 6‑month enhanced maternity leave and 4 weeks fully‑paid paternity leave.
- Help finding great childcare with funded hours via Koru Kids.
- Look after the pennies
- Competitive pension offering with standard and salary sacrifice options.
- Success is best when it's shared
- Quarterly away days with the whole UK team.
- Quarterly team social budget.
- Social activities and celebrations on our gorgeous rooftop in King's Cross.
- #J-18808-Ljbffr