Sr. Data Engineer - FP&A

What Cognite is:Relentlessto achieve

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements.

We thrive in challenges. We challenge assumptions. We execute with speed and ownership. If you view obstacles as signals to step forward - not backwards - you’ll feel right at home here. 

Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

Cognite operates at the forefront of industrial digitalization, building AI, and data solutions that solve the world’s hardest, highest-impact problems. With unmatched industrial heritage and a comprehensive suite of AI capabilities, including low-code AI agents, Cognite accelerates the digital transformation to drive operational improvements. We thrive in challenges. We challenge assumptions. We execute with speed and ownership. Our Moonshot is bold: Unlock $100B in customer value by 2035, and redefine how global industry works. Join us in this venture where AI and data meet ingenuity, and together, we will forge the path to a smarter, more connected industrial future.

We're looking for a Senior Data Engineer with business acumen who is ready to tackle big challenges and advance their career. In this role, you'll join a team committed to creating cutting-edge business solutions that significantly impact critical business functions across Cognite. You will report to the Vice President of FP&A (Financial Planning & Analysis) and be tasked with building out the Cognite Enterprise Data Warehouse (EDW) for business data. This will include building the Semantic (logic/contextualization) layer for business data and leading the selection and implementation of a world class EDW AI solution. You'll collaborate with Finance, Sales, Marketing, P&O/HR, Legal, Engineering, etc. to deploy and optimize digital solutions that empower users to make better data-driven business decisions.

If you're passionate about leveraging technology to solve tough problems and are eager to impact the way Cognite operates, we want to hear from you. Let's build the future of Cognite business data, reporting and AI capabilities together.

Strategy & architecture

• Lead the design and implementation of a scalable Enterprise Data Warehouse (EDW) and efficient data engineering solutions using Azure, Fabric, Power BI, and Cognite Data Fusion®.
• Technology Selection: Evaluate and select data technologies, frameworks, and platforms to support future business scaling needs.

Build & integration

• Drive and manage integrations, extractions, data modeling, and analysis using data connectors and SQL, Python/Java, and REST APIs.
• Data Pipeline Development: Develop and maintain data pipelines (ETL/ELT) to move data from source systems into data warehouses or data lakes.
• Data Preparation: Clean, transform, and aggregate raw data into structured formats optimized for Power BI reporting and AI agents.
• Data Modeling: Create custom data models for data discovery, mapping, and cleansing. Define conceptual, logical, and physical data models to map out how different data entities relate to one another.

Operations & enablement

• Governance & Security: Establish standards for data quality, security, privacy, and compliance (e.g., GDPR, CCPA).
• Collaborate with business stakeholders and engineering organizations to enable data-driven business decisions.

Job Requirements

Education & background 

• Bachelor's or Master's degree in computer science or a related field; relevant experience may compensate for formal education. A business degree (MBA) or demonstrated experience working in finance, sales, marketing, supply chain, or a similar business setting is strongly preferred.

Experience 

• Minimum 5 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 administration tasks such as subscription management and Key Vault; familiarity with GCP is a plus.
• Experience with Microsoft Fabric, including Lakehouse architecture, Notebooks (PySpark, Spark SQL, DAG workflows), and PowerShell scripting.
• Experience building and maintaining Power BI semantic models (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 ramp quickly on Cognite Data Fusion (CDF), including Python SDK, Flows/Dune, and GraphQL

Mindset & ways of working 

• DevOps mindset with experience across CI/CD pipelines and deployment environments.
• Able to independently investigate and solve complex data problems with minimal direction.
• Comfortable working in cross-functional teams spanning both technical and business stakeholders.
• Demonstrates humility - willing to ask for help and actively shares knowledge with others.

A snapshot of our many perks and benefits as a Cogniter

* Competitive compensation

* 401(k) with employer matching

* Competitive health, dental, vision & disability coverages for employees and all dependents

* Unlimited PTO

* Paid Parental Leave Program

* Employee Referral Program

Learn more about us

• Impact 2025
• Cognite's Industrial AI: Moonshot
• We’re globally recognized domain experts with an international presence that spans Phoenix, Houston, Oslo Tokyo, Bengaluru, and Abu Dhabi.

Equal Opportunity

Cognite is committed to creating a diverse and inclusive environment at work and is proud to be an equal opportunity employer. All qualified applicants will receive the same level of consideration for employment.