Senior Data Scientist, Full Stack

Context: Help modernize global Supply Chain systems and the data tools portfolio by shaping data architecture, tooling standards, and ways of working at IREN.

Responsibilities

• Design, build, and maintain reliable ELT/ETL pipelines from supply chain source systems into the analytics platform (ERP; procurement/P2P; inventory and warehouse; project controls; logistics and supplier portals).
• Integrate external datasets including supplier catalogs, lead-time and market-price feeds, freight and customs data, and OEM shipment notifications.
• Own pipeline orchestration, scheduling, monitoring, and alerting so data lands on time and failures are detected before users are impacted.
• Build and document a supply chain data model spanning supplier, material/part, purchase order, contract, receipt, inventory, shipment, and project/site dimensions and facts.
• Define and align conformed dimensions and master-data rules (supplier hierarchy, category taxonomy, site and project codes) with the Director, Data Analytics and master-data owners.
• Set and enforce engineering standards across the team, 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 data catalog to support analyst and business-user trust and discovery.
• Determine and implement a security model based on privacy requirements, ensure safeguards are followed, address data quality issues, and evolve governance processes within owned 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 visualization reporting supporting multiple use cases across different domains.
• Build data foundations for forecasting and planning use cases (demand and lead-time forecasting, should-cost, supplier risk) and support data science teams in productionizing models.
• Contribute to system selection and implementation work (procurement, planning, and supplier-management tools) by defining data requirements and integration patterns.

Requirements

• Bachelor’s degree in computer science, engineering, information systems, supply chain, or a related field, or equivalent practical experience.
• 8+ years in data engineering, including at least 2 years building pipelines and data models for supply chain, procurement, operations, or finance data.
• Ability in data-driven storytelling for a broad stakeholder team and audience.
• Strong understanding of supply chain processes, tools, stakeholder interactions, and experience with ERP/MRP, CLM, PLM, QMS tools.
• Expert SQL and strong Python; comfortable 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).
• Hands-on experience with AI-native analytics.
• Experience integrating ERP and procurement systems (e.g., SAP, Oracle, NetSuite, Dynamics, Coupa, Ariba) via APIs, extracts, or CDC.
• Solid grounding in dimensional modeling, master-data concepts, and data-quality practices.
• Software engineering discipline including Git, CI/CD, automated testing, and basic infrastructure-as-code.
• Preferred: experience in data center, AI infrastructure, energy, construction, or other capital-project-heavy industries with long-lead equipment (GPUs, networking, transformers, switchgear, generators).
• Must be able to reliably commute to the assigned office location on scheduled in-office days under the hybrid work arrangement.
• Willingness to travel domestically and internationally to supplier and vendor sites, data centers, implementation partner locations, and industry events.
• Pre-employment screening may be required, including background check and substance testing, per company policies.

Technologies

• SQL, Python, dbt
• Snowflake, Databricks, BigQuery, Redshift
• Airflow, Dagster, Prefect
• Git, CI/CD, infrastructure-as-code
• ELT, ETL, APIs, CDC
• SAP, Oracle, NetSuite, Dynamics, Coupa, Ariba

Location

• San Francisco, CA (hybrid)

Salary

• USD 225,000 - 285,000 per year (expected base salary)

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 available
• 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 to support certifications, continuing education, or role related training
• Company events and team-building activities
• Total Compensation package may include annual incentive bonus and equity (long-term incentive)
• Relocation or Living-out-allowance / per diem (as applicable and based on successful candidate circumstances)

Additional work arrangement and screening notes

• Pre-employment screening may include background check and substance testing per company policies.
• IREN does not yet have an office in the Bay Area (a Santa Clara office is planned). Until it opens, this role will work remotely and transition to hybrid on-site work once the office is established.