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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 our 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 modeling 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-modeled 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
- Keeping BigQuery costs in check
- Contribute to data governance, including:
- Documentation
- Naming standards
- Discoverability
- Exploring how emerging AI tooling can strengthen the data platform
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What Does Success Look Like in Your First 3 Months?
You’ll have:
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A solid understanding of the existing dbt project, data models, and key reporting areas
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Started working independently on modeling tasks with minimal direction
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Shipped well-structured, tested dbt models that analysts and stakeholders can trust and use
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Identified at least one area of the warehouse to meaningfully improve
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Built effective working relationships with:
- The BI team
- The Data Platform Lead
- Backend engineers
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Stayed ahead of schema changes rather than reacting to them in an ad-hoc manner
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Documentation and governance contributions will be in place, making it easier for the team to build on your work.
Must-Haves
- 4+ years of hands-on dbt Core experience in a production environment
- Proficient in SQL and comfortable with modern data warehouse concepts:
- Dimensional modeling
- Layered architecture
- Practical experience with cloud data warehouses, ability to:
- Write efficient queries
- Understand performance improvements
- 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:
- Pull requests
- Code reviews
- Contributing to team coding standards
- Takes ownership of data quality in the models they build:
- Proactively identifying and resolving issues
- Avoiding treatment as a “someone else’s problem”
- Curiosity about AI applications in data, including:
- Emerging tooling
- Semantic layers and their role in building intelligent data products
Nice-to-Haves
- Experience with dbt Cloud and BigQuery, particularly:
- Scheduling
- Orchestration
- Warehouse optimization
- Familiarity with Tableau or supporting analysts using BI tools
- Experience building semantic layers, with knowledge of their role in:
- Supporting LLM and AI applications
- Experience with CDC pipelines or event-driven data architectures
- Python for data transformation or automation tasks
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About JustPark
We invest in your well-being and career growth so you can focus on what matters outside of work too.
Recharge Your Batteries
- Generous holiday policy: 25 days + bank holidays + up to 5 extra days for high performance (total of 38 days per 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 per year for eye tests
- Free O2 concert tickets via 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:
- 6 months enhanced maternity leave
- 4 weeks fully paid paternity leave
- Help finding great childcare with funded hours via Koru Kids
Look After the Pennies
- Competitive pension offering:
- Standard contribution
- 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
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First-stage: 30-minute virtual video interview via Google Meet with the People Team to discuss:
- More about JustPark and the role
- Your experience in detail
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Second-stage: 45-minute virtual video interview via Google Meet with the Hiring Manager
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Third-stage: Take-home technical task
- Always relevant for the role and designed for efficiency
- Length varies by role/seniority but will not exceed 3–4 hours
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Final-stage: 1-hour final interview in our King’s Cross office
- Questions on your task approach, learnings, and typical interview-style questions
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