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Data Quality Analyst
Alfred H Knight. Profile, harmonise, audit, and clean large, fragmented, multi-source datasets .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in SQL and Python for data manipulation and quality assurance, with a strong ability to bridge technical and business operations. Proven experience in managing multi-source datasets and establishing data standards across cross-functional teams.
Highest-signal resume keywords
SQL Query WritingPython ProficiencyData Profiling ToolsMaster Data Management ExperienceData Quality Analysis
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
SQLPythonData ProfilingData CleaningData AnalysisMulti-Table JoinsAggregationsWindow FunctionsData Quality RulesBatch Processing
Soft Skills
CommunicationCollaborationProblem-SolvingAttention to DetailInvestigative Skills
Tools & Technologies
Microsoft PurviewSemarchyReltioInformatica MDMProfiseeSAP MDG
Industry Keywords
Master Data ManagementData QualityISO 17025ISO 9001LIMS SoftwareRegulatory ComplianceData GovernanceData StewardshipData DiscrepanciesLegacy Systems
Tech Stack
Tools & technologiesInformaticaNumpyPandasPythonSQL
About the role
Key responsibilities & impact- Profile, harmonise, audit, and clean large, fragmented, multi-source datasets
- Work with data from over 40 regional system instances
- Act as a technical bridge between business operations and IT
- Work directly with business Data Owners and Data Stewards
- Feed high-quality, standardised data into the enterprise Master Data Management platform
- Enable accurate global reporting and strategic decision-making across 35+ countries
- Establish shared data standards with cross-functional and multi-regional teams
- Translate operational rules and regulatory compliance requirements into technical Data Quality rules
Requirements
What you’ll need- Proven, hands-on experience writing SQL queries, scripts, and routines to extract, profile, audit, and clean large, multi-source datasets
- Experience with multi-table joins, aggregations, and window functions
- Practical proficiency in Python, including tools such as Pandas and NumPy, for data manipulation, batch processing, and automation
- Demonstrable experience using data profiling tools such as Microsoft Purview or similar
- Working knowledge of or exposure to an enterprise Master Data Management platform, such as Semarchy, Reltio, Informatica MDM, Profisee, or SAP MDG
- Ability to explain technical data quality issues clearly to non-technical business stewards and operational leads
- Structured, persistent approach to investigating data discrepancies across fragmented legacy systems
- Comfortable working alongside cross-functional and multi-regional teams to establish shared standards
- Ability to translate operational rules and regulatory compliance requirements into technical Data Quality rules
- Practical experience in a Data Quality, Data Analysis, or Data Support role within a complex, multi-system business environment
- Experience working with unnormalised legacy database structures, inconsistent formatting, and disparate data sources
- Exposure to Testing, Inspection, and Certification, laboratory environments, LIMS software, or ISO 17025 / 9001 frameworks is advantageous
- Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related quantitative discipline, or equivalent practical industry experience
Benefits
Comp & perks- Pension
- Life assurance
- Employee assistance programme
- Reasonable adjustments to the recruitment process where needed