Job description

We are seeking a graduate-level intern to join our Talent Acquisition (TA) team as a Talent Acquisition Data Engineering & Analytics Intern. This role is designed for a highly motivated individual who wants hands-on experience building and analyzing TA metrics that influence business decisions at a global scale. The intern will learn how to extract, transform, and visualize data from multiple HR and business systems while contributing to the foundation of our global TA reporting function. The Talent Acquisition Data Engineering & Analytics Intern will build the production reporting layer for Talent Acquisition. This internship is designed for a technically strong graduate student who wants to own the full path from raw recruiting data to automated, leadership-facing dashboards. The intern will establish Snowflake connectivity and automated data refresh, build a query-ready data model, and develop a complete Power BI dashboard suite covering all Talent Acquisition metrics. The intern will work directly with Talent Acquisition leadership and collaborate with the teams responsible for SmartRecruiters, Workday, Jira, ServiceNow, and Snowflake. This internship focuses on data engineering, data modeling, dashboard development, and reporting automation, rather than operational recruiting activities. Key Responsibilites • Establish and validate connections between Talent Acquisition source systems and Snowflake, partnering with Data Engineering and 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 before leadership sees them. • Build a query-ready dimensional data model in Snowflake supporting recruiting 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. • 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. • Create end-user guides and deliver enablement sessions for TA Operations and HR leadership. • Partner with Talent Acquisition leadership to prioritize requirements, translate business questions into measurable metrics, and present dashboard walkthroughs and insights. Example Internship Deliverables • Operational Snowflake data pipeline supporting Talent Acquisition reporting • Dimensional data model deployed in Snowflake • Complete Power BI dashboard suite covering the Talent Acquisition metrics framework • Governed semantic model with certified, documented measures • Automated refresh configuration with monitoring and data quality validation • Technical documentation, refresh runbook, and end-user enablement materials • Recommended roadmap for future Talent Acquisition analytics development • Currently pursuing a graduate degree in Data Analytics, Data Science, Data Engineering, Computer Science, Information Systems, or a related field. • Strong proficiency in SQL, including joins, aggregations, window functions, and query optimization. • Hands-on experience building dashboards in Power BI, including DAX measures and data modeling. • Experience with Python or R for data extraction, transformation, and analysis. • Working knowledge of dimensional data modeling and dataset design principles. • Familiarity with ETL/ELT concepts and building or maintaining data pipelines. • Ability to translate ambiguous business questions into structured, measurable analytics requirements. Preferred Qualifications • Hands-on experience with Snowflake or a comparable cloud data warehouse (BigQuery, Redshift, Databricks). • Experience configuring automated refresh, scheduled jobs, or orchestration tooling (dbt, Airflow, Azure Data Factory). • Experience with Power BI Service administration: workspaces, gateways, deployment pipelines, or row-level security. • Experience with APIs or system-to-system data integrations. • Experience with large datasets in cloud environments (Azure, AWS, or GCP). • Exposure to version control (Git) and analytics engineering practices. • Familiarity with AI/ML techniques and interest in applying them to workforce data. • Passion for HR, Talent Acquisition, or workforce analytics and how data informs business strategy. • This role is eligible for remote work, with a strong preference for candidates in the Pacific, Mountain, or Central time zone. • Candidates should be comfortable working with confidential candidate and employee data in accordance with Solidigm data privacy and handling standards. Target Start Date = October 2026 Internship Length = 6 months, part-time basis (20 hours per week) Location = Flexible to be remote or hybrid if local to a Solidigm worksite Powered by SmartRecruiters - Candidate Privacy Policy

Requirements

Must-haves

This internship focuses on data engineering, data modeling, dashboard development, and reporting automation, rather than operational recruiting activities.
Key Responsibilites
Establish and validate connections between Talent Acquisition source systems and Snowflake, partnering with Data Engineering and 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 before leadership sees them.
Build a query-ready dimensional data model in Snowflake supporting recruiting 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.
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.
Create end-user guides and deliver enablement sessions for TA Operations and HR leadership.
Partner with Talent Acquisition leadership to prioritize requirements, translate business questions into measurable metrics, and present dashboard walkthroughs and insights.

Nice-to-haves

Hands-on experience with Snowflake or a comparable cloud data warehouse (BigQuery, Redshift, Databricks).
Experience configuring automated refresh, scheduled jobs, or orchestration tooling (dbt, Airflow, Azure Data Factory).
Experience with Power BI Service administration: workspaces, gateways, deployment pipelines, or row-level security.
Experience with APIs or system-to-system data integrations.
Experience with large datasets in cloud environments (Azure, AWS, or GCP).
Exposure to version control (Git) and analytics engineering practices.
Familiarity with AI/ML techniques and interest in applying them to workforce data.
Passion for HR, Talent Acquisition, or workforce analytics and how data informs business strategy.
Candidates should be comfortable working with confidential candidate and employee data in accordance with Solidigm data privacy and handling standards.
Target Start Date = October 2026
Internship Length = 6 months, part-time basis (20 hours per week)
Location = Flexible to be remote or hybrid if local to a Solidigm worksite

Application prep

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Keywords to mirror

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Platform: smartrecruiters
Effort: medium