Sr. Data Engineer - FP&A

Cognite$100K — $140K *
Enterprise Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in computer science or a related field; MBA preferred.
  • Minimum 5 years experience in data-intensive roles, ideally customer-facing.
  • Proven track record in developing production-grade data pipelines using Python, SQL, and REST APIs.
  • Hands-on experience with Azure services and familiarity with GCP.
  • Experience with Microsoft Fabric and Power BI semantic models and reports design.
  • Proficiency in GitHub for version control and Terraform for infrastructure management.
  • Willingness to learn Cognite Data Fusion and related technologies.

Responsibilities

  • Lead design and implementation of a scalable Enterprise Data Warehouse (EDW).
  • Evaluate and select data technologies to support business scaling.
  • Manage data integrations, modeling, and analysis using SQL and Python/Java.
  • Develop and maintain ETL/ELT data pipelines from source systems to warehouses.
  • Clean and transform raw data into structured formats for reporting.
  • Create custom data models to aid data discovery and cleansing.
  • Establish standards for data quality, security, and compliance.

Benefits

  • Competitive health, dental, vision & disability coverages for employees and all dependents.
  • 401(k) with employer matching.
  • Unlimited Paid Time Off (PTO).
  • Paid Parental Leave Program.
  • Employee Referral Program.
Full Job Description
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

About Cognite

Cognite is a technology company that provides industrial data management and analytics solutions. The company's platform allows businesses to collect, process, and analyze data from industrial equipment and systems. Cognite's solutions help businesses optimize their operations, reduce costs, and improve safety. The company was founded in 2017 and is headquartered in Oslo, Norway.
Learn more about Cognite
Size
500 employees
Industry
Founded
2017

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