Analytics Engineer

About JustPark

JustPark 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.

We've always believed parking should be easier, from end to end. That's why we, two trailblazing companies - ParkHub and JustPark - have come together to make that vision a reality.

ParkHub revolutionized event parking in the US, optimizing venue operations for a smoother, stress-free experience. JustPark transformed parking in the UK, turning the hunt for a spot into a simple, seamless task.

Now, as one unified company, we're combining expertise to offer a full-service, frictionless parking solution for both businesses and consumers.

About the Role

The Analytics Engineer is a hands-on technical role within JustPark's data team, sitting at the intersection of data engineering and analytics. You'll 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'll help translate raw data into trusted, scalable assets that shape how JustPark makes decisions.

This is an ideal role for someone who is fluent in dbt and BigQuery, enjoys owning modelling problems end-to-end, and can hit the ground running in a fast-moving product environment.

Responsibilities

• Build, test, and document dbt models in BigQuery 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 BigQuery costs in check
• Contribute to data governance: documentation, naming standards, discoverability, and exploring how emerging AI tooling can strengthen the data platform

What does success look like in your first 3 months?

• You'll have a solid understanding of the existing dbt project, data models, and key reporting areas, and is working independently on modelling tasks with minimal direction
• You shipped well-structured, tested dbt models that analysts and stakeholders can trust and use, and identified at least one area of the warehouse to meaningfully improve
• You built effective working relationships with the BI team, Data Platform Lead, and backend engineers, staying ahead of schema changes rather than reacting to them
• Documentation and governance contributions are in place, making it easier for the team to build on the work going forward

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 BigQuery, 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

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 YuLife
• £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 JustPark
• 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-months 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

Our Interview Process

• First-stage - 30-minute virtual video interview via Google Meet with the People Team to tell you more about JustPark and the role and learn more about your experience
• Second-stage - 45-minute virtual video interview via Google Meet with the Hiring Manager
• Third-stage - Take home task - We always make sure that the task is relevant for the role and as efficient as possible. Our tasks vary in length based on role & seniority but the task wouldn’t take longer than a max. of 3-4 hours to complete
• Final stage - A 1 hour final interview in our lovely office in Kings Cross, where the team will ask you some questions on your task approach, any learnings and wider final interview-type questions