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Solidigm

Talent Acquisition Graduate Intern, Data Engineering & Analytics

Solidigm

. Establish and validate connections between Talent Acquisition source systems and Snowflake .

Posted 10/2/2026part-timeRemote • California • United StatesEntry Level💰 $50 per hourWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong proficiency in SQL and Power BI for data analysis and visualization, with hands-on experience in building dashboards and implementing data quality checks. Capable of translating business requirements into structured analytics and managing data pipelines in cloud environments like Snowflake.

Highest-signal resume keywords
SQL ProficiencyPower BI Dashboard DevelopmentDimensional Data ModelingData Pipeline ManagementData Privacy Compliance

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills
SQLDAXData ModelingETL/ELT ConceptsPythonRData TransformationQuery OptimizationData Quality ChecksData Analysis
Soft Skills
Analytical ThinkingCommunicationCollaborationProblem-SolvingAdaptability
Tools & Technologies
Power BISnowflakeAzure Data FactoryAirflowDbtAPIs
Industry Keywords
Talent AcquisitionWorkforce AnalyticsData PrivacyData GovernanceAnalytics Engineering

Tech Stack

Tools & technologies
AirflowAWSAzureCloudETLGoogle Cloud PlatformPythonSQL

About the role

Key responsibilities & impact
  • Establish and validate connections between Talent Acquisition source systems and Snowflake
  • Configure Power BI connectivity and scheduled refresh
  • Implement data quality checks and refresh monitoring
  • Build a query-ready dimensional data model in Snowflake
  • Write and optimize SQL transformations for analysis-ready tables and historical reporting
  • Develop Power BI dashboards covering executive summaries, requisition and pipeline health, funnel conversion, time-to-fill, time-in-stage, offer metrics, sourcing effectiveness, recruiter workload, and TA operational SLA metrics
  • Build a governed semantic model with certified DAX measures
  • Implement row-level security and optimize model performance
  • Produce documentation covering pipeline architecture, data lineage, model diagrams, measure definitions, and troubleshooting
  • Create end-user guides and deliver enablement sessions for TA Operations and HR leadership
  • Partner with Talent Acquisition leadership to prioritize requirements and translate business questions into metrics
  • Present dashboard walkthroughs and insights
  • Deliver an operational Snowflake pipeline, dimensional model, Power BI dashboard suite, automated refresh monitoring, technical documentation, enablement materials, and a future analytics roadmap

Requirements

What you’ll need
  • 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
  • Comfortable working with confidential candidate and employee data in accordance with Solidigm data privacy and handling standards
  • Preferred: hands-on experience with Snowflake or a comparable cloud data warehouse
  • Preferred: experience configuring automated refresh, scheduled jobs, or orchestration tooling such as dbt, Airflow, or Azure Data Factory
  • Preferred: experience with Power BI Service administration, including workspaces, gateways, deployment pipelines, or row-level security
  • Preferred: experience with APIs or system-to-system data integrations
  • Preferred: experience with large datasets in Azure, AWS, or GCP
  • Preferred: exposure to Git and analytics engineering practices
  • Preferred: familiarity with AI/ML techniques and workforce data
  • Preferred: passion for HR, Talent Acquisition, or workforce analytics

Benefits

Comp & perks
  • Remote work eligibility
  • Flexible remote or hybrid arrangement if local to a Solidigm worksite
  • Part-time schedule of 20 hours per week
  • Hands-on experience with global-scale Talent Acquisition data engineering and analytics
  • Direct collaboration with Talent Acquisition leadership and cross-functional technical teams
  • Enablement and professional development through documentation, guides, and sessions