Data Engineer - London

Description


Title: R&D Data Engineer
Role location: Old Street, London, UK
Department: Research & Development 
Reports to: VP, R&D

[The right candidate must be immediately available or ready to start early August]

About WiredScore

Founded in 2013, WiredScore is the leading certification body for digital connectivity and smart building performance. The company has offices in New York, London, Paris, Frankfurt, Singapore, Hong Kong, and Mumbai. We work with over 1,000 of the world’s leading real estate owners and developers—including 8 of the 10 largest landlords in the world—certifying more than 1 billion square feet across 45 countries. Today, over 9 million people live and work in WiredScore-certified buildings globally.

In 2026, WiredScore joined forces with Meter, a leading provider of enterprise internet infrastructure. deepening WiredScore’s connection to the technology that powers digital connectivity in buildings

What we do

Connectivity is now as critical to buildings as power or water, but delivering it has historically been fragmented, complex and inconsistent.  

WiredScore was created to solve this. We own and operate two products:

• WiredScore certification, the first and only rating system for mobile and internet connectivity in buildings, helping landlords assess, improve, benchmark, and promote their buildings
• SmartScore, the smart building certification, helping landlords understand, improve, and communicate the user functionality and technological foundations of their buildings

Meter builds and operates integrated networking infrastructure across internet, wired, Wi-Fi, and cellular, combining hardware, software, deployment, and ongoing operations into a single solution. Meter is backed by Sequoia, Microsoft, General Catalyst, and individual investors like Sam Altman, headquartered in San Francisco, and currently supports institutions like Bridgewater, Lyft, and Reddit to keep their thousands of employees and locations online and productive.

Together, WiredScore and Meter are defining the next era of connectivity in real estate.
It’s an exciting time to join WiredScore, you will be part of a high-impact R&D team shaping the data foundation of a fast-growing, global business that is shaping how an entire industry thinks about connectivity and bringing a fundamentally new proposition to market.

Requirements

We’re looking for an inquisitive, meticulous and self-motivated Data Engineer to help build out the data foundation for WiredScore’s next stage of growth. You’ll help scale our existing data platform to turn data from our certification products, customer systems, websites, and operational tools into reliable, well-modelled datasets that support reporting, product development, client insight, and market analysis.

This is a hands-on role in the R&D team, working closely with our Senior Data Solutions Architect and colleagues across Product, Client Success, Marketing, RevOps, and Engineering. You’ll help execute the Product and R&D data roadmap by making our data accurate, usable, governed, and ready to support new data-led products and decision-making across the business.

Must have

• Strong SQL and Python knowledge.
• Experience building reliable ETL/ELT pipelines.
• Experience working with relational, analytical, or lakehouse data platforms.
• Hands-on experience with Microsoft Fabric and Power BI.
• Good understanding of data modelling and medallion architecture, such as raw, cleaned, and business-ready datasets.
• Strong data quality mindset, including testing, validation, and monitoring.
• Ability to translate business requirements into clear technical solutions.
• Clear communication with technical and non-technical stakeholders.

Nice to have

• Integration experience with GA4, BigQuery, Salesforce, Pardot, Marketing Cloud.
• Data governance or catalogue tools such as Azure Purview, Unity Catalog, or Apache Atlas.
• CI/CD development and automated testing.
• dbt and orchestration tools.
• Web analytics and product event tracking.
• Data preparation for AI, ML, or data science use cases.