Senior Data Analyst

About Supplier.io

Supplier.io is the data foundation that enterprises build their supplier decisions on. Fragmented, duplicated, and unreliable supplier data quietly limits the ROI of source-to-pay platforms, analytics, risk, and AI initiatives, so we resolve, enrich, and continuously maintain the industry's most complete supplier identity, then put it to work for the teams that buy and the suppliers themselves. Relied on by companies across the Fortune 2000 for accurate data, our platform helps corporate procurement, finance, and compliance teams manage their vendor master, source diverse and sustainable suppliers, and mitigate risk, all from one verified identity instead of a dozen disconnected systems.

Our solutions turn that foundation into action: accurate data and continuous maintenance for teams managing a fragmented vendor master, sourcing intelligence built resolving even the hardest-to-identify suppliers, small, local, and diverse businesses, for teams tracking sustainability and compliance, and direct visibility for the suppliers themselves into where they stand with the enterprises that buy from them. Whether you're resolving vendor records, sourcing alternatives, or measuring program results, Supplier.io transforms complexity into clarity, so teams can lead with confidence and build supply chains that deliver for both business and community.

For more information, visit www.supplier.io.

The Opportunity

The Senior Data Analyst owns data quality for our Supplier data as part of our new Data Enablement function. You'll evaluate whether the output of our data engine is correct, complete, and trustworthy, and own the analytical work of linking our registry backbone to supplementary data sources.

Data Enablement sits alongside Data Engineering: you'll partner closely with its Director and the data and ETL engineers on technical execution, while also working with Product and other cross-functional teams to insights and surface new opportunities in the data.

What You Will Do

Data Quality Ownership

• Own the analytical data-quality work for our Supplier data: profiling, sampling, issue quantification, and recommendations to engineering.
• Drive source linking across our registry backbone and supplementary sources (such as S&P Capital IQ, GLEIF, and SAM), and help define a systematic approach to resolving conflicts between sources.
• Define and monitor quality dimensions (completeness, freshness, accuracy), and help build the automated quality gates that don't exist today.
• Prioritize quality effort toward the subset of entities customers actually interact with most.

Cross-Functional Insight & Opportunity-Finding

• Partner with the Director of Data Engineering and the data and ETL engineers to translate quality findings into technical fixes and prioritized work.
• Work with Product and other cross-functional teams to data insights and help identify new opportunities in the data, beyond quality alone.
• Build and maintain dashboards and reports that give visibility into data health across the platform.
• Bring a customer's-eye view to quality prioritization and to product improvements like TrustIQ, informed by direct experience with how customers actually use the data.

What You Will Need to Succeed

• Strong SQL and BigQuery (or equivalent) data-analysis skills, with hands-on data-quality and profiling experience across multiple external data sources.
• Comfortable working across both data warehouse and data lake environments (Snowflake), with hands-on experience using analysis and dashboarding tools built on top of them (such as Looker, Tableau, or Mode) to surface and communicate findings.
• Familiarity with dbt or similar transformation tools is an asset, not a requirement.
• Customer-facing or implementation background that supports quality prioritization from a user's perspective.
• Comfort partnering across engineering, product, and other cross-functional teams to findings and influence priorities.

Nice to Have

• Direct experience with legal-entity or supplier data sources (OpenCorporates, S&P Capital IQ, GLEIF, SAM, or similar registries).
• Working knowledge of master data management and entity/source-linking challenges (tax IDs, DUNS, name and address matching).
• Experience building or defining automated data-quality gates or monitoring.

Where You Fit In

You'll sit within Data Enablement, working closely with the Director of Data Engineering, Data Architect and the data and ETL engineers on technical execution, and with Product and other cross-functional teams on sharing insights and finding new opportunities in the data. For now, you'll report directly to the CTO while Data Enablement's leadership structure is built out.

We do not accept unsolicited resumes from recruitment/search firms.

AI Use Policy:

The use of artificial intelligence tools during your interview is strictly prohibited. This includes, but is not limited to, AI chatbots, real-time answer generators, transcription-based assistants, and any other software that generates or suggests responses. Any detected use of AI during the interview will result in immediate disqualification and removal from consideration for this position.

Supplier.io participates in E-Verify. For more information, click here. We will provide the Social Security Administration and, if necessary, the Department of Homeland Security, with information from each new employee’s Form I-9 to confirm work authorization.

Supplier.io is an Equal Employment Opportunity employer. All qualified applicants will receive consideration for employment without regard to race color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.