Description
About Dwelly
Dwelly is building the AI operating system for residential lettings. Its growing network of agencies provides its AI with real-world data, continuous feedback, and control over complete workflows, making exceptional service the standard for landlords and tenants. Today, Dwelly operates more than 15,000 properties and $470 million in GMV, making it one of the UK’s ten largest lettings operators. The company has raised $263 million.
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 Quality Analyst to own the validation and quality assurance of data migrations into Dwelly.
Your primary responsibility will be reviewing and approving CRM data migrations before they reach production. You'll work closely with backend engineers and migration tooling to ensure imported data is complete, accurate, and internally consistent.
This role combines advanced SQL, data analysis, automated validation, and investigation of real-world data quality issues. You'll design validation queries, identify inconsistencies, investigate unexpected results, and help improve our migration tooling over time.
The ideal candidate has exceptional attention to detail, enjoys investigating data problems, and is comfortable making release decisions based on evidence.
We’re hiring remotely across the UK, Ireland, and European time zones. Candidates should be based within these regions/time zones to enable effective collaboration with the wider team.
Key Responsibilities
- Data Migration Validation
Review and approve CRM migration datasets before production deployment by validating completeness, consistency, and overall data quality. - Production Data Quality
Review production data updates and validate SQL scripts before execution to ensure large-scale changes are safe and correct. - Data Integrity Verification
Develop automated validation queries that detect missing records, duplicate entities, broken relationships, and other integrity issues across migrated datasets. - Migration Reconciliation
Compare source CRM exports with Dwelly data to verify successful migration and investigate discrepancies. - Data Investigation
Analyse unexpected migration results, identify root causes of inconsistencies, and work with engineers to resolve complex data issues. - Continuous Quality Improvement
Identify recurring migration issues and help improve migration processes, validation tooling, and overall data quality standards.
Qualifications and Preferred Background
- Strong SQL skills, including complex joins, CTEs, aggregations, window functions, and update scripts
- Experience validating production data or large database migrations
- Strong understanding of relational databases and data integrity principles
- Experience investigating inconsistencies across large datasets
- Comfortable comparing data from multiple systems and identifying discrepancies
- Ability to design automated validation checks instead of relying on manual inspection
- Excellent analytical and problem-solving skills
- Strong ownership mindset with the confidence to approve or reject production data changes
- Exceptional attention to detail
- Ability to work independently in ambiguous situations
- Ability to effectively use modern AI development tools (such as ChatGPT, Claude, GitHub Copilot, Cursor, Codex, or similar) to improve productivity, investigate data issues, generate SQL, automate repetitive tasks, and accelerate analysis while maintaining high standards of accuracy and review.
Technical Environment
- PostgreSQL
- MySQL
- DuckDB (testing and validation)
- Git
- SQLMesh or dbt
- Dolt or similar version-controlled database technologies
- CSV-based CRM migrations
Nice to Have
- Python for automation and data analysis
- Experience building automated data quality frameworks
- Knowledge of ETL or ELT pipelines
- Experience working with CRM migrations or property management systems
- Familiarity with data observability and reconciliation tooling
What Success Looks Like
- Production migrations are approved with confidence and minimal manual effort.
- Automated validation catches the vast majority of migration issues before deployment.
- Data integrity issues are identified early and resolved quickly.
- Migration quality improves continuously through better validation and investigation.
- Engineers trust the migration approval process because it is evidence-driven, repeatable, and reliable.
Compensation & Benefits:
- Fully remote role.
- Competitive compensation based on experience and impact.
- Opportunity to work on high-leverage automation systems at the intersection of backend engineering, applied ML, data and real operational workflows.
- 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 about solving one of the world’s most complex problems in the largest consumer industry in the world: residential rentals.
More than 30% of households live in rental homes — over 5 million in the UK and more than 100 million across the EU and US. Our mission is to improve that experience through technology, automation and operational excellence.
This is about disrupting one of the largest and most antiquated industries in the world with one of the strongest operational and technical teams in the UK and Europe.
We work hard, and we aim for extremely ambitious results. We want people to be proud of what they’ve built and to one day look back and say: “Hell yeah, that was me that did it.”
Our Principles
- Customer obsession rather than competitive focus
- Passion for invention
- Operational excellence
- Long-term thinking
By applying for this position, you consent to the processing and storage of your personal data for recruitment purposes for up to 365 days, in accordance with our data retention policy and applicable data protection laws.
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