I

IREN

Operates renewable-powered AI GPU cloud infrastructure

Senior Data Scientist - Full Stack

Data EngineeringConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$225k - $285k /yr

About the Job

Requirements

  • A bachelor's degree in computer science, engineering, information systems, supply chain, or a related field, or equivalent practical experience.
  • At least 8 years of data engineering experience, including at least 2 years building pipelines and data models for supply chain, procurement, operations, or finance data.
  • Ability to use data-driven storytelling for a broad stakeholder team and audience.
  • Strong understanding of supply chain processes, tools, and stakeholder interactions, and experience with ERP/MRP, CLM, PLM, and QMS tools.
  • Expert SQL skills and strong Python skills; familiarity with dbt or an equivalent transformation framework.
  • Hands-on experience with a modern cloud data platform such as Snowflake, Databricks, BigQuery, or Redshift and an orchestration tool such as Airflow, Dagster, Prefect, or similar.
  • Hands-on experience with AI-native analytics.
  • Experience integrating ERP and procurement systems such as SAP, Oracle, NetSuite, Dynamics, Coupa, or Ariba through 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 infrastructure-as-code basics.
  • Ability to reliably commute to the assigned office 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.
  • Pre-employment screening, including a background check and substance testing, may be required according to company policies.

Responsibilities

  • Design, build, and maintain reliable ELT/ETL pipelines from supply chain source systems, including ERP, procurement/P2P, inventory and warehouse, project controls, logistics, and supplier portals, into the analytics platform.
  • Integrate external data such as 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 arrives on time and failures are identified before users see them.
  • Build and document the supply chain data model, including supplier, material/part, purchase order, contract, receipt, inventory, shipment, and project/site dimensions and facts.
  • Define conformed dimensions and master-data rules, including supplier hierarchy, category taxonomy, and site and project codes, with the Director, Data Analytics, and master-data owners.
  • Set and enforce team engineering standards for version control, code review, testing, environments, and deployment.
  • Implement automated data-quality checks for completeness, freshness, and 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.
  • Determine and implement the security model based on privacy requirements, confirm safeguards are followed, address data-quality issues, and evolve governance processes within allocated ownership areas.
  • Partner with analysts to deliver datasets behind spend cubes, supplier scorecards, lead-time and on-time-delivery tracking, inventory health, and transformation KPIs.
  • Design, build, and launch dashboards and visualization reporting that support multiple use cases across different domains.
  • Build data foundations for forecasting and planning use cases, including demand and lead-time forecasting, should-cost, and supplier risk, and support analytics and data science teammates in productionizing models.
  • Contribute to system-selection and implementation work for procurement, planning, and supplier-management tools by defining data requirements and integration patterns.

Desired Qualifications

  • Experience in data center, AI infrastructure, energy, construction, or other capital-project-heavy industries with long-lead equipment such as GPUs, networking, transformers, switchgear, and generators.

About the Company

IREN

Operates renewable-powered AI GPU cloud infrastructure

IREN runs renewable-powered AI cloud and digital infrastructure by operating data centers and GPU clusters. Customers access high-performance NVIDIA GPUs and AI training/inference infrastructure through cloud-based services powered by grid-connected and renewable energy assets. It differentiates itself through full vertical integration of energy assets with compute infrastructure and a focus on North America. The company aims to provide scalable, renewable-powered AI compute for enterprises and developers to support large-scale AI workloads.

Company size
501-1,000
Company stage
IPO
Headquarters
Sydney NSW, Australia
Founded
2018

Recently Posted Jobs

Explore more opportunities at IREN

See more jobs