Data Quality Analyst

Job Description:

• We are seeking a contract data analyst to support complex data quality, coverage, and
• cross-source comparison work across multiple enterprise datasets. This role will focus on
• evaluating data consistency, identifying gaps and mismatches across systems, and
• helping translate business rules into reliable facts from imperfect source data. The ideal
• candidate is strong in SQL and data analysis, comfortable working through ambiguity,
• curious about learning the business domain, and proactive about engaging domain experts
• when needed to validate assumptions or findings.

Key Responsibilities

• Perform data quality, coverage, and comparison analysis across multiple internal data sources
• Assess consistency, completeness, and reliability of identifiers and cross-system relationships
• Analyze ambiguous or conflicting source records and help determine fit for business use cases
• Apply and refine business rules to derive usable facts from noisy, incomplete, or inconsistent data
• Compare new datasets against existing sources to identify strengths, weaknesses, and coverage tradeoffs
• Support exploratory analysis in Databricks and contribute to basic ETL-oriented data investigation workflows
• Produce clear analysis, recommendations, and validation findings for business and technical stakeholders
• Partner with domain experts and reach out when needed to validate uncertain outputs or business interpretations
• Document assumptions, logic, data issues, and decision frameworks in a structured way

Required Skills and Experience

• Strong SQL skills and experience analyzing large, messy enterprise datasets
• Experience with data quality assessment, data profiling, and reconciliation across multiple systems
• Hands-on experience with Databricks
• Working knowledge of basic ETL concepts and data flow validation
• Ability to work with ambiguous source data and infer reliable patterns using business logic
• Familiarity with graph-style representations of complex data models or ontologies
• Strong analytical thinking with attention to detail and comfort investigating edge cases
• Curiosity about learning unfamiliar business domains quickly
• Willingness to chase clarity by engaging with domain experts directly rather than making unsupported assumptions
• Ability to communicate findings clearly to both business and technical audiences

Preferred Qualifications

• Experience working with enterprise data domains such as ERP, HR, CRM, or Billing
• Experience using Python, notebooks, or BI tools for exploratory analysis and reporting
• Experience documenting business rules, exceptions, and source-system behavior in a structured way
• Exposure to enterprise platform data is a plus What Success Looks Like
• Clear assessment of data quality and coverage across key source datasets
• Actionable recommendations on which data sources and mappings are fit for operational use
• Improved confidence in derived facts across inconsistent enterprise data
• Well-documented findings, business rules, and validation methodology