Talent Acquisition Graduate Intern, Data Engineering & Analytics

This is a fully remote position, open to applicants in California.

📋 Description

• Establish and confirm connections between Talent Acquisition source systems and Snowflake.

• Set up Power BI connectivity along with scheduled refresh functionalities.

• Execute data quality checks and monitor refresh processes.

• Develop a query-optimized dimensional data model in Snowflake.

• Write and enhance SQL transformations for tables ready for analysis and historical reporting.

• Create Power BI dashboards that include executive summaries, requisition and pipeline health, funnel conversion rates, time-to-fill, time-in-stage metrics, offer metrics, sourcing effectiveness, recruiter workloads, and TA operational SLA metrics.

• Construct a governed semantic model featuring certified DAX measures.

• Implement row-level security and enhance model performance.

• Produce documentation that details pipeline architecture, data lineage, model diagrams, measure definitions, and troubleshooting processes.

• Develop end-user guides and conduct enablement sessions for TA Operations and HR leadership.

• Collaborate with Talent Acquisition leadership to prioritize needs and convert business inquiries into measurable metrics.

• Present dashboard walkthroughs and insights.

• Deliver an operational Snowflake pipeline, a dimensional model, a comprehensive Power BI dashboard suite, automated refresh monitoring, technical documentation, enablement materials, and a future analytics roadmap.

⛳️ Requirements

• Currently enrolled in a graduate program in Data Analytics, Data Science, Data Engineering, Computer Science, Information Systems, or a related discipline.

• Strong expertise in SQL, encompassing joins, aggregations, window functions, and query optimization.

• Practical experience in creating dashboards using Power BI, including DAX measures and data modeling.

• Proficiency in Python or R for data extraction, transformation, and analysis.

• Working understanding of dimensional data modeling and principles of dataset design.

• Familiarity with ETL/ELT concepts and the construction or maintenance of data pipelines.

• Ability to interpret vague business questions into structured, measurable analytics requirements.

• Comfortable handling confidential candidate and employee information in line with Solidigm's data privacy and handling protocols.

• Preferred: Practical experience with Snowflake or a similar cloud data warehouse.

• Preferred: Experience in configuring automated refreshes, scheduled jobs, or orchestration tools like dbt, Airflow, or Azure Data Factory.

• Preferred: Knowledge of Power BI Service administration, encompassing workspaces, gateways, deployment pipelines, or row-level security.

• Preferred: Experience with APIs or system-to-system data integrations.

• Preferred: Background working with large datasets in Azure, AWS, or GCP.

• Preferred: Exposure to Git and analytics engineering methodologies.

• Preferred: Familiarity with AI/ML techniques and workforce data.

• Preferred: A strong interest in HR, Talent Acquisition, or workforce analytics.

🏝️ Benefits

• Eligibility for remote work.

• Flexible remote or hybrid work arrangement if located near a Solidigm office.

• Part-time commitment of 20 hours per week.

• Practical experience with global-scale Talent Acquisition data engineering and analytics.

• Direct collaboration with Talent Acquisition leadership and interdisciplinary technical teams.

• Opportunities for enablement and professional growth through documentation, guides, and sessions.