JOB SUMMARY
Build and deliver the production reporting layer for Talent Acquisition on a contract basis. Own the full path from raw recruiting data to automated, leadership-facing dashboards - establishing cloud data warehouse connectivity and automated refresh, designing and deploying a query-ready dimensional data model, and developing a complete Power BI dashboard suite covering the Talent Acquisition metrics framework. Serve as the technical lead for data engineering, data modeling, dashboard development, and reporting automation. This role does not include operational recruiting activities.
Key Responsibilities
• Establish and validate connections between Talent Acquisition source systems (SmartRecruiters, Workday, Jira, ServiceNow) and the cloud data warehouse, partnering with Data Engineering and IT.
• Build and maintain production-grade ELT pipelines, including API-based ingestion where source systems require it.
• Configure Power BI connectivity and scheduled refresh so dashboards update automatically without manual data pulls.
• Implement data quality checks and refresh monitoring so reporting issues surface and are remediated before leadership sees them.
• Design, build, and deploy a query-ready dimensional data model supporting requisition, funnel, and hiring activity analytics.
• Write and optimize SQL transformations that turn raw source system data into analysis-ready tables, including historical and point-in-time reporting such as requisition status history and pipeline snapshots.
• Define table grain, conformed dimensions, and slowly changing dimension patterns appropriate to recruiting workflows.
• Develop a full Power BI dashboard suite covering the Talent Acquisition metrics framework, including executive summary, requisition and pipeline health, funnel conversion, time-to-fill and time-in-stage, offer metrics, sourcing effectiveness, recruiter workload, and TA operational SLA metrics.
• Build a governed semantic model with certified DAX measures so metrics are defined once and consumed consistently across all reporting.
• Implement row-level security and optimize model performance at full data volume.
• Produce implementation-ready documentation covering pipeline architecture, data lineage, model diagrams, measure definitions, and a refresh and troubleshooting runbook.
• Establish metric definitions and secure stakeholder agreement on contested or ambiguous definitions before publication.
• Create end-user guides and deliver enablement sessions for TA Operations and HR leadership.
• Deliver a documented handover so teams can operate and extend the solution after the engagement ends.
• Partner with Talent Acquisition leadership to prioritize requirements, translate business questions into measurable metrics, and present dashboard walkthroughs and insights.
• Operate independently with limited day-to-day oversight, proactively surfacing risks, dependencies, and trade-offs.
Required Qualifications
• Bachelor's degree in Data Analytics, Data Science, Data Engineering, Computer Science, Information Systems, or a related field; or equivalent practical experience.
• 4+ years of professional experience delivering production analytics or data engineering solutions.
• Advanced SQL, including complex joins, aggregations, window functions, and query optimization against large datasets.
• Demonstrated Power BI delivery experience, including authoring DAX measures, designing semantic models, and publishing to Power BI Service.
• Hands-on experience with a cloud data warehouse platform (e.g., BigQuery, Redshift, Databricks, Snowflake, or comparable).
• Proven experience designing and implementing dimensional data models in a production environment.
• Experience building and maintaining ETL/ELT pipelines, including incremental loads and failure handling.
• Proficiency in Python (or R) for data extraction, transformation, and analysis.
• Demonstrated ability to translate ambiguous business questions into structured, measurable analytics requirements and to drive stakeholder agreement on metric definitions.
• Experience documenting technical solutions and enabling non-technical end users.
Preferred Qualifications
• Experience with Snowflake.
• Experience with Power BI Service administration: workspaces, gateways, deployment pipelines, and row-level security.
• Experience with orchestration and transformation tooling (dbt, Airflow, Azure Data Factory).
• Experience with APIs and system-to-system data integrations.
• Experience with HR or Talent Acquisition source systems, particularly SmartRecruiters or Workday.
• Experience with Workday Prism Analytics or Workday Data Cloud.
• Experience with large datasets in cloud environments (Azure, AWS, or GCP).
• Proficiency with version control (Git) and analytics engineering practices.
• Prior experience delivering analytics solutions in a contract or consulting capacity, including structured handover.
• Familiarity with AI/ML techniques and interest in applying them to workforce data.
• Interest in HR, Talent Acquisition, or workforce analytics and how data informs business strategy.
