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Cognite

Industrial data platform with AI

Senior Data Scientist

Data EngineeringUpdated on Nov 14
Full-timePhoenix, AZ, USANo salary listedIn-person

About the Job

Requirements

  • A bachelor's or master's degree in computer science or a related field is required, though relevant experience may compensate for formal education.
  • At least five years of experience in internal or external customer-facing, data-intensive roles.
  • Proven experience delivering production-grade data pipelines using Python, SQL, and REST APIs.
  • Hands-on experience with Azure cloud services, including subscription management and Key Vault administration.
  • Experience with Microsoft Fabric, including Lakehouse architecture, Notebooks (PySpark, Spark SQL, and DAG workflows), and PowerShell scripting.
  • Experience building and maintaining Power BI semantic models using star schema and designing reports for business stakeholders.
  • Proficiency with GitHub for version control, GitHub Actions for CI/CD, and Terraform for infrastructure and access management.
  • Willingness to learn and quickly ramp up on Cognite Data Fusion, including its Python SDK, Flows/Dune, and GraphQL.
  • Experience with CI/CD pipelines and deployment environments.
  • Ability to independently investigate and solve complex data problems with minimal direction.
  • Ability to work in cross-functional teams spanning technical and business stakeholders.

Responsibilities

  • Lead the design and implementation of a scalable Enterprise Data Warehouse and efficient data engineering solutions using Azure, Fabric, Power BI, and Cognite Data Fusion.
  • Evaluate and select data technologies, frameworks, and platforms to support future business scaling needs.
  • Drive and manage integrations, extractions, data modeling, and analysis using data connectors, SQL, Python or Java, and REST APIs.
  • Develop and maintain ETL/ELT data pipelines to move data from source systems into data warehouses or data lakes.
  • Clean, transform, and aggregate raw data into structured formats optimized for Power BI reporting and AI agents.
  • Create custom data models for data discovery, mapping, and cleansing, and define conceptual, logical, and physical data models that map relationships between data entities.
  • Establish standards for data quality, security, privacy, and compliance, including GDPR and CCPA.
  • Collaborate with business stakeholders and engineering organizations to enable data-driven business decisions.

Desired Qualifications

  • A business degree (MBA) or demonstrated experience working in finance, sales, marketing, supply chain, or a similar business setting is strongly preferred.
  • Familiarity with GCP.

About the Company

Cognite

Industrial data platform with AI

Cognite provides cloud-based data and AI platforms for industrial companies to digitize and optimize operations. Its flagship Cognite Data Fusion connects OT, IT, and engineering data, unifying sensor data, maintenance logs, and 3D models into a real-time view of assets to improve performance and safety. Cognite Atlas AI is a low-code platform that lets engineers build AI agents for predictive maintenance, anomaly detection, and production optimization without deep coding. The company differentiates itself through deep cross-domain data integration for asset-heavy industries and a scalable cloud environment to accelerate industrial digitalization and deliver measurable value.

Company size
501-1,000
Company stage
Acquired
Total funding
$225.3M
Headquarters
Tempe, AZ
Founded
2016

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