ironquill.tech/board

$ cat jobs/data-quality-analyst-dwelly-fe8719553c43.json

Data Quality Analyst

dwelly·UK·United Kingdom·mid
sql
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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 result

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