LONDON, WATERLOO (HYBRID, 4 DAYS IN-OFFICE - WEDNESDAY IS OUR SET WORK FROM HOME DAY, THOUGH YOU CAN COME IN ON WEDNESDAY TOO IF YOU WISH)

We’re a VC backed, disruptive technology business with a purpose to make the world fairer and more productive. We are doing this by making assets more transparent, trustworthy and accessible - starting with real estate. Incomes have stagnated and we believe by creating greater access to high value assets like real estate we believe we can be part of solving some of the wealth inequality. Our investment platform is focussed on one of the largest asset classes in the world - property. We are gaining significant momentum with our portfolio of products focused on the UK property investment market.
Our CEO and Founder Moubin previously worked at McKinsey and private equity firm APAX. Check out a podcast with Moubin speaking with our lead investors QED about how we’re disrupting asset ownership.
Our four values are the foundation of our culture and shape our behaviours - no BS, pursuit of excellence, feedback obsession and healthy ego. We have built a high performing organisation where intrinsic drive fuels GetGrounders to build a world class investment experience for our users.

In numbers:

• 85+ GetGrounders (ex Google, Meta, Deliveroo, Startups)
• £1.5Bn+ of assets being added onto our platform annually
• 30,000+ users across 70 countries, with ~10% market share
• Global hubs (UK, Dubai, Hong Kong, Singapore, Philippines)

SKILLS AND EXPERIENCE YOU WILL HAVE:

• You’ve worked in a Data/Analytics Engineering role previously
• Highly competent with SQL and dbt
• Experience building business reports using a BI tool (e.g. Looker, Tableau, Lightdash or PowerBI)
• Experience working with stakeholders across different areas in the business, understanding their data needs and translating them into data insights
• Proactive and independent, you take initiative to identify and solve problems, and deliver solutions with little guidance

WHAT YOU WILL DO:

• Work closely with different teams across the business to provide clean, timely, reliable data to answer to their business needs
• Transform and model new and existing data sources using dbt, BigQuery, Looker/LookML and other tools
• Work across all stages of the data lifecycle, including building and maintaining data pipelines, designing and modeling datasets, and creating insightful dashboards for data visualization.
• Bring software engineering principles to the data stack including version control, continuous integration, unit testing & documentation