This individual-contributor role supports modernization of IREN’s global Supply Chain systems. The position focuses on building and operating data pipelines, data models, dashboards, and contributing to data architecture and standards across supply chain and procurement analytics.
Role Overview
The work spans supply chain, procurement, ERP and integration, data quality and governance, and analytics enablement for planning and forecasting use cases. Reporting to the Director, Supply Chain Analytics & Engineering, you will build reliable data flows from operational sources into an analytics platform and partner with analysts and data science teammates to deliver decision-ready datasets.
Responsibilities
- Design, build, and maintain reliable ELT/ETL pipelines from supply chain source systems (ERP, procurement/P2P, inventory and warehouse, project controls, logistics, and supplier portals) into the analytics platform.
- Integrate external data sources including supplier catalogs, lead-time and market-price feeds, freight and customs data, and OEM shipment notifications.
- Operate and improve pipeline orchestration, scheduling, monitoring, and alerting to ensure timely data delivery and early failure detection.
- Build and document the supply chain data model, including supplier, material/part, purchase order, contract, receipt, inventory, shipment, and project/site dimensions and facts.
- Help define conformed dimensions and master-data rules (supplier hierarchy, category taxonomy, site and project codes) under the guidance of the Director, Supply Chain Analytics & Engineering and master-data owners.
- Follow and refine team engineering standards including version control, code review, testing, environments, and deployment.
- Implement automated data-quality checks (completeness, freshness, reconciliation to source) and publish data-quality metrics.
- Maintain data lineage, definitions, and a catalog so analysts and business users can trust and find the data.
- Implement the defined security model and privacy safeguards, address data-quality issues, and contribute to governance processes within assigned ownership areas.
- Partner with analysts to deliver datasets for spend cubes, supplier scorecards, lead-time and on-time-delivery tracking, inventory health, and transformation KPIs.
- Design, build, and launch dashboards and visualizations supporting multiple use cases across different domains.
- Contribute to forecasting and planning data foundations (demand and lead-time forecasting, should-cost, supplier risk) and support analytics and data science teams in productionizing models.
- Support system-selection and implementation work for procurement, planning, and supplier-management tools by defining data requirements and integration patterns.
Required Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Supply Chain, or a related field, or equivalent practical experience.
- 5+ years in data engineering or data science, including at least 1 year building pipelines and data models for supply chain, procurement, operations, or finance data.
- Strong data-driven storytelling skills for communicating clearly to both technical and business audiences.
- Working understanding of supply chain processes and stakeholder interactions, with experience using ERP/MRP and tools such as CLM, PLM, and QMS.
- Strong SQL and Python; familiarity with dbt or an equivalent transformation framework.
- Hands-on experience with a modern cloud data platform (Snowflake, Databricks, BigQuery, or Redshift) and an orchestration tool (Airflow, Dagster, Prefect, or similar).
- Exposure to AI-native analytics tools and workflows.
- Experience working with ERP and procurement data (for example SAP, Oracle, NetSuite, Dynamics, Coupa, or Ariba) via APIs, extracts, or CDC.
- Working knowledge of dimensional modeling, master-data concepts, and data-quality practices.
- Software engineering fundamentals including Git, code review, automated testing, and CI/CD basics.
- Preferred: experience in data center, AI infrastructure, energy, construction, or other capital-project-heavy industries with long-lead equipment (GPUs, networking, transformers, switchgear, generators).
- Strong hands-on problem solving, data analysis, and communication skills with the ability to operate autonomously across analytics, engineering, and supply chain teams.
Technologies
SQL, Python, dbt, Snowflake, Databricks, BigQuery, Redshift, Airflow, Dagster, Prefect, SAP, Oracle, NetSuite, Dynamics, Coupa, Ariba, ELT/ETL, APIs, CDC, Git, CI/CD, ERP/MRP, CLM, PLM, QMS
Compensation
The expected base salary range for this role is USD $190,000 to $240,000 per year. The total compensation package may include an annual incentive bonus and equity (long-term incentive). Relocation or living-out allowance/per diem may be provided when applicable and based on candidate circumstances.
Benefits
- 100% company-paid health insurance premiums (medical, dental, and vision) for employees; 75% company-paid coverage for dependents.
- Company-paid short-term and long-term disability insurance.
- Voluntary life, critical illness, and accident coverage.
- Health Savings Accounts (HSA) when combined with the High Deductible Health Plan.
- Employee Assistance Program and wellness resources.
- 401(k) retirement plan with company match.
- Access to financial planning and legal services.
- Paid Time Off (PTO) and paid holidays.
- Internal skills training and advancement pathways.
- Professional development support for certifications, continuing education, or role-related training.
- Company events and team-building activities.
Job Type and Location
- Job Type: Full-Time
- Location: San Francisco, CA (hybrid)
- Work Location Type: #hybrid
Additional Job Requirements
- Pre-employment screening, including background check and substance testing, may be required according to company policies.
- Must be able to reliably commute to the assigned office location on scheduled in-office days under the hybrid arrangement.
- Willingness to travel domestically and internationally to supplier and vendor sites, data centers, implementation partner locations, and industry events is required.
- IREN does not yet have an office in the Bay Area (a Santa Clara office is planned). Until it opens, this role will be remote and will transition to hybrid on-site work once the office is established.
