Job Opportunities API

About Dwelly Dwelly is a UK-based, AI-enabled lettings and property management platform growing through a roll-up strategy by acquiring estate agencies and integrating them into a modern technology platform. As we acquire agencies, we inherit large volumes of operational data from different CRM systems. Every migration introduces differences in data quality, structure, and completeness. Maintaining high-quality production data is critical to ensuring a reliable customer experience. 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. 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