Metadata Governance and Data Sourcing Lead

JobTarget is a leading company in the online job search and recruiting industry. Our team is comprised of experts in recruitment, e-commerce, and online job search. Our products are used by thousands of corporate recruiters and reach millions of job seekers.

We are seeking a forward-thinking and highly organized Leader of Metadata Governance and Data Sourcing to play a foundational role in our data infrastructure. In this role, you’ll be responsible for acquiring and enhancing third-party data sources and ensuring the integrity and usability of these data assets. You will also lead our data parsing systems, ensuring high-quality structured data flows into downstream systems such as search, reporting, analytics, and AI models. 

Metadata Governance & Reference Data Management 

• Own and maintain core data structures across: 
• Job Titles / Topic Model / Job Functions 
• Skills and Skill-Title Relationships 
• Company and Industry Metadata 
• Location Hierarchies and Coordinates 
• ATS and Job Board Profiles 
• Job Application and Disposition Metadata 
• Resume Metadata and Career Progression Patterns 
• Define standards, taxonomies, and entity relationships across these datasets and ensure they are properly documented and versioned. 

Data Sourcing & Acquisition 

• Identify, assess, and onboard 1st- and 3rd-party data from a variety of sources (customers, partners, vendors, public datasets). 
• Partner with Legal and Engineering to manage data agreements, ingestion pipelines, and usage policies. 
• Work with external vendors (e.g., BLS, PDL, Resume Library, LinkedIn, Aspen, Jobspikr) and internal integrations (ATS feeds, career site scrapes). 

Parser Operations (Resumes and Job Descriptions) 

• Serve as operational owner for our parsing systems for resumes and job descriptions. 
• Ensure parsing tools are accurate, performant, and regularly updated to reflect evolving job market and resume trends. 
• Collaborate with the Data team to optimize the parsing pipeline and post-processing logic. 
• Monitor structured output quality and coordinate QA testing and vendor issue resolution. 

Data Integration & Quality Management 

• Design and maintain processes for linking, deduplicating, and enriching data across systems. 
• Define and enforce data quality rules for entity resolution (e.g., linking jobs ↔ resumes ↔ applications). 
• Ensure datasets are consistently accessible and integrated across analytics, product, and ML pipelines. 

Cross-Functional Enablement 

• Enable Product, Engineering, Sales, and Data Science teams to build features and intelligence off reliable metadata. 
• Support use cases such as search filtering, job-candidate matching, salary insights, programmatic bidding, and customer-facing analytics. 
• Act as the go-to SME for foundational data integrity across the platform.