Supplier.io is the market leader in supplier intelligence, trusted by over half of the Fortune 100 to power smarter, more responsible sourcing decisions. Our platform helps corporate procurement teams discover, evaluate, and engage with over 11 million suppliers with a focus on local, small, diverse, and sustainable businesses. This helps organizations build supply chains that are resilient, inclusive, and built for impact.
Our solutions empower today’s procurement teams with accurate data, actionable insights, and measurable impact, which helps them mitigate risk, expand sourcing options, achieve ESG goals, and advance economic inclusion. Whether tracking spend, sourcing alternate suppliers, or measuring program results, Supplier.io transforms complexity into clarity; empowering teams to lead with confidence and build supply chains that deliver for both business and community.
Join a company committed to innovation, inclusion, and making a difference one sourcing decision at a time. For more information, visit www.supplier.io.
Position Summary
The Data Operations Specialist will work as part of the supplier.io Atlas Delivery Team responsible for preparing, processing, auditing, and verifying data delivered to supplier.io's internal and external customers. This role primarily follows structured workflows and detailed instructions to review, analyze, and validate business-related data across multiple data projects. The Data Operations Specialist evaluates match accuracy, conducts external research to validate company identities and firmographic attributes, and applies sound judgement to ensure data quality standards are maintained. The role requires strong analytical thinking, proficiency in Excel and basic SQL, and the ability to investigate and resolve data-related issues.
Key Responsibilities
Data Matching and Validation
- Review, analyze and verify match results across company profiles
- Confirm that company attributes such as legal name, address, and corporate identifiers accurately align with the matched entity
- Apply sound reasoning and judgement to determine match validity and escalate ambiguous or complex cases when necessary
- Maintain consistent data quality standards across enrichment projects
Company Research and Data Verification
- Conduct research using search engines, AI tools, company registries, and public data sources to verify company identities and firmographic attributes
- Validate company hierarchy relationships including parent companies, subsidiaries, and ultimate ownership structures
- Confirm company profile information such as industry classification, location, and firmographic characteristics
- Document analyst decision logic to support development of automated matching algorithms and LLM-based data enrichment tools.
Data Analysis and Excel Management
- Work with datasets in Excel to perform data review, filtering, summarization, and analysis
- Manipulate and structure data to support enrichment workflows and quality validation
- Analyze company profile and firmographic datasets to identify inconsistencies, suspicious data or anomalies
Data Querying and Investigation
- Use basic SQL queries to retrieve and validate data from internal systems, including Snowflake and MySQL databases
- Investigate data discrepancies between input files, enrichment outputs, and internal databases
Issue Resolution and Troubleshooting
- Identify data-related issues that may impact match accuracy or enrichment results
- Troubleshoot root causes and recommend potential solutions or workarounds based on data knowledge and analysis
- Collaborate with internal teams when technical or systemic issues are identified
Documentation and Communication
- Document research findings, data and match validation decision logic to support development of automated matching algorithms and LLM-based data enrichment tools
- Provide transparency through clear updates on project status, findings, and issues to management
- Communicate effectively with internal teams to clarify requirements and resolve data questions
Required Qualifications
Technical Skills
- Strong proficiency in Microsoft Excel to support data analysis using shortcuts and formula functions
- Basic knowledge of SQL, including the ability to run queries to retrieve and analyze data
- Familiarity with data quality validation and data matching concepts
Analytical Skills
- Strong attention to detail with the ability to evaluate complex company data relationships
- Ability to apply reasoning and judgement when validating company matches and resolving ambiguous cases
- Ability to analyze structured data and identify inconsistencies or anomalies
Research and Investigation
- Experience researching companies using online sources, registries, and AI tools
- Ability to verify company identity, firmographic attributes, and corporate hierarchies
Communication
- Excellent written and verbal communication skills
- Ability to clearly communicate and document findings, processes, and project updates
Preferred Qualifications
- Experience working with firmographic data, supplier intelligence data, or company master data
- Familiarity with data enrichment, entity resolution, or company matching processes
- Experience querying Snowflake or other cloud data platforms
- Experience working with company hierarchy or corporate ownership data
