Data Platform Lead

About Dwelly

Dwelly — a UK-based, AI-enabled lettings and property management platform, that is growing through a roll-up strategy acquiring estate agencies. The company leverages two arms: i) acquiring existing letting agencies, effectively buying its highly sticky, recurring revenue-type landlords portfolios, and then ii) building a top-notch technology to automate tenant management, payments, and post-rental property maintenance. The company seamlessly integrates AI services to automate all business processes within brick-and-mortar real estate agencies, integrating them into a tech-enabled digital letting platform in two months to radically improve the user experiences and increase efficiency of the business.

We’re a fast-growing, product-focused company, backed by top-tier investors and led by a team with deep experience in real estate, technology, and operations.

Position Summary

We’re looking for a Data Platform Team Lead to own and build our data engineering function. You will be the second hire on the team, with two additional engineers to be hired under your leadership. As the team is still small, we expect you to be hands-on and spend around 40–50% of your time writing code and designing systems.

This role is mission-critical and covers three core areas of the business:

Key Responsibilities:

1. CRM Integration & Data Ingestion

Each business we acquire uses a different real estate CRM system (one of the top-10 most widely used in the UK). Your team will be responsible for building custom data extraction tools for each CRM — extracting lease contracts, landlord and tenant data, financial records, and more — and piping that into our systems. This will involve:

• Reverse-engineering or working with APIs/databases of major CRM vendors
• Designing modular, maintainable ingestion services
• Automating “one-click” data exports for seamless onboarding

2. Data Architecture, Optimization & Compliance

• Design and maintain a unified data architecture: database schemas, data models, and micro-architecture solutions to ensure scalability and reliability.
• Optimize database performance at all levels: indexing, partitioning, clustering, and tuning configuration parameters.
• Ensure full compliance with GDPR, UK Data Protection Act, and other relevant regulations: data masking, consent management, retention policies, and privacy impact assessments.

3. Data Infrastructure, Analytics Platform & Ops Automations

You’ll also lead the buildout of our central analytics infrastructure, making it easy for our operations, finance, and DS teams to get the insights they need. This includes:

• Building production processes with complex logic, for example, using CV libraries and flexible cloud expansion for quick recalculations of historical data. The calculation logic and python notebooks will be provided by DS, your responsibility is to wrap it up as a production pipeline.
• Design and maintain a unified data architecture: database schemas, data models, and micro-architecture solutions to ensure scalability and reliability.
• Optimize database performance at all levels: indexing, partitioning, clustering, and tuning configuration parameters.
• Designing and maintaining robust ETL/ELT pipelines for different sources and different types of data, including phone calls, emails, scrapping public reviews, еtс.
• Building and optimizing our data warehouse on BigQuery
• Setting up foundational data governance practices (lineage, quality checks, cost monitoring, etc.)
• Choosing the right tools from the Google Cloud stack and applying them effectively to balance performance, cost, and maintainability.
• Ensure full compliance with GDPR, UK Data Protection Act, and other relevant regulations: data masking, consent management, retention policies, and privacy impact assessments.

 Qualifications & Preferred Background:

• Turn ideas into clean, structured, and elegant code.
• Designed and implemented systems that were adopted by your team.
• Experience with different data pipeline technologies and understanding of their trade-offs (message queues, distributed systems, data warehouses, orchestration tools).
• Solved complex performance optimization challenges in data pipelines.
• Practical experience monitoring data quality effectively.
• Solid grasp of core data warehouse design patterns and ability to communicate in “SA language” fluently.
• Experience leading teams or projects in larger organizations, with hands-on experience across cloud platforms (Google Cloud, AWS, Azure).
• Built complex pipelines integrating diverse technologies (e.g., image/audio analysis, cascading ML libraries, LLM APIs).
• Experience setting up CI/CD pipelines and processes.
• Strong communication skills and fluency in English.
• Startup mentality: resilience, adaptability, and ability to thrive in a fast-paced environment.
• Customer-centric mindset: focus on delivering value to end-users or clients.
• Strong problem-solving skills – ability to approach challenges logically and propose practical solutions.

Compensation & Benefits:

• The role is fully remote, providing flexibility and enabling seamless collaboration with our geographically distributed team.
• Competitive salary with the potential for equity options based on performance, recognising exceptional contributions to our integration success.

What is it like being a Dwell-er?

Feel free to check out Dwelly Core Principles. That’s about what we believe in, how we operate and make decisions.

What we offer is not a fancy office or a static workplace. Instead, this is solving one of worlds’ most complex problems in the largest consumer industry in the world (residential rentals), to improve the experience for >30% of households (>5M in the UK, and >100M including EU and US) that live in rental homes.

This is about disrupting the largest, most antiquated industry in the world, with one of the strongest operational and technical teams that exist in the UK and the EU. We work hard, and we shoot for extremely ambitious results. But we want people to be proud of what they’ve built and be able to look back and say one day “hell yeah, that was me that did it all”.

• Customer obsession rather than competitive focus
• Passion for invention
• Operational excellence
• Long-term thinking