Data Engineer - Talent Acquisition Operations

The Role

As a Data Engineer, you will help to build and maintain the data foundations, reporting workflows, and automations that support Recruiting and Hiring Operations. This role will work cross-functionally with Hiring Operations, Recruiters, Data, Security, Privacy, and other technical and non-technical partners to turn complex recruiting processes into reliable datasets, dashboards, and operational tools.

Core Responsibilities

• Build, maintain, and improve datasets and pipelines supporting Recruiting.
• Integrate data from systems such as Lever, Workday, Foundry, and other recruiting systems.
• Develop reporting datasets and dashboards for recruiting performance, candidate pipelines, recruiting programs, and operational audits.
• Evaluate existing data integrations for opportunities to reduce latency and implement necessary changes.
• Partner with central Data and platform teams on warehouse connections, schema changes, API behavior, and source-system migrations.
• Support integrations between recruiting systems and internal tools including writeback of data updates.
• Design data access and reporting solutions that respect confidentiality, role-based permissions, and regional or organizational access boundaries.
• Create clear documentation for sensitive workflows and ensure that operational users understand the limitations of the data.
• Proactively identify opportunities to improve reporting and workflows as recruiting processes change.
• Partner with team members, engineering, product, and business leaders to understand current user behavior and patterns across our platform.
• Monitor pipelines for stability, suggest and implement efficiency initiatives.

What We Value

• Proven ability to build and maintain data pipelines, datasets, and analytics data products.
• Hands-on experience with Foundry, Contour, or comparable data and analytics platforms.
• Background working with Recruiting, HR, People, CRM, ATS, or other operational data; Lever experience preferred.
• Proficiency integrating APIs, data warehouses, and SaaS systems.
• Familiarity with workflow automation, writeback processes, and event-driven integrations.
• Working knowledge of data governance, privacy, retention, access controls, and compliance-related workflows.

What We Require

• Degree in Data Science, Finance, Math, Engineering, Computer Science, Economics, Business, or other quantitative fields.
• 1+ years of experience in a data analytical role.
• Expertise in Python and data manipulation to answer complex questions. Experience with pySpark, pandas, or polars is a plus.
• Strong SQL skills and experience working with relational or structured data.
• Proficiency with BI tools, SQL, and the organization and analysis of data.
• Fluency in TypeScript, or another general-purpose programming language.
• Ability to create reusable data models, testing frameworks, and data quality checks.