Talent Acquisition Data Engineering & Analytics Specialist

Talent Acquisition Data Engineering & Analytics Specialist (Contract)

Location: San Jose, CA, or Rancho Cordova, CA, hybrid three days per week preferred. Fully remote in PST may be considered for a very strong candidate.

Contract Duration: Contract through June 2027, with potential extension

Employment type: W2 through staffing supplier

Pay rate: $65.00/hour

Visa sponsorship: Not available

We’re seeking a hands-on Talent Acquisition Data Engineering & Analytics Specialist to build a reliable, automated reporting foundation for Talent Acquisition. You’ll work across data pipelines, cloud data warehousing, dimensional modeling, and Power BI—turning recruiting data into trusted, leadership-ready insights.

This is a technical analytics role, not an operational recruiting position. You’ll partner with Talent Acquisition leaders and Data Engineering, IT, and HRIS teams to define useful metrics, deliver production reporting, and equip internal teams to maintain and extend the solution.

What you’ll do

• Connect Talent Acquisition source systems—including platforms such as SmartRecruiters, Workday, Jira, and ServiceNow—to a cloud data warehouse, in partnership with Data Engineering and IT.
• Build and maintain production ELT pipelines, including API-based ingestion where needed.
• Design and deploy a query-ready dimensional data model for requisition, recruiting funnel, and hiring activity analysis.
• Write and optimize SQL transformations, including historical and point-in-time reporting.
• Develop a Power BI dashboard suite covering executive summaries, requisition and pipeline health, funnel conversion, time-to-fill, time-in-stage, offers, sourcing, recruiter workload, and operational service levels.
• Build a governed semantic model with clearly defined DAX measures so metrics are consistent across reports.
• Configure automated refresh and implement data-quality checks and monitoring.
• Document architecture, data lineage, models, measure definitions, and troubleshooting procedures.
• Work with stakeholders to agree on metric definitions, present dashboards and insights, and enable business users.
• Deliver knowledge transfer, operational handover, and recommendations for future analytics development.
• Assess relevant Workday Prism Analytics, Workday Data Cloud, and Power BI enhancements within the project scope.

What you’ll bring

• Bachelor’s degree in a relevant field or equivalent practical experience.
• 4+ years of professional experience delivering production analytics or data engineering solutions.
• Advanced SQL skills, including complex joins, aggregations, window functions, and query optimization.
• Hands-on Power BI experience with DAX, semantic models, and publishing to Power BI Service.
• Experience with a cloud data warehouse and production dimensional data modeling.
• Experience building and supporting ETL/ELT pipelines, including incremental loads and failure handling.
• Proficiency in Python or R for data extraction, transformation, or analysis.
• Strong stakeholder skills: able to turn broad business questions into measurable requirements and resolve ambiguity in metric definitions.
• Experience documenting solutions and helping non-technical users adopt them.
• Good judgment when working with confidential candidate and employee data.

Preferred experience

• Snowflake.
• Power BI Service administration, including workspaces, gateways, deployment pipelines, and row-level security.
• dbt, Airflow, or Azure Data Factory.
• APIs and system integrations.
• Workday, SmartRecruiters, or other HR and Talent Acquisition systems.
• Workday Prism Analytics or Workday Data Cloud.
• HR, Talent Acquisition, or workforce analytics.
• Git, analytics engineering practices, and structured contract or consulting handovers.
• Familiarity with AI/ML applications to workforce data.

What success looks like

• Automated daily data refresh supporting production reporting.
• A dimensional model validated with stakeholders.
• A Power BI suite that Talent Acquisition leaders actively use.
• Reliable reporting, documented metric definitions, and clear support procedures.
• A successful handover that enables internal teams to operate and extend the solution.

The role involves confidential candidate and employee data and requires responsible handling in line with applicable data privacy standards.