Job Description
Job Description
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