Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Senior Data Engineer - FP&A
USA (Phoenix)
Open 4 months, first seen by us 125 days ago- Pay
- Pay not listedSimilar roles state $127K–$190K
- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingLead design and build of a scalable Enterprise Data Warehouse on Azure and Fabric
Develop and maintain ETL/ELT pipelines from source systems into warehouses or lakes
Clean and aggregate raw data into structures optimized for Power BI and AI agents
Create conceptual, logical and physical data models for business entities
Set standards for data quality, security, privacy and compliance
From the employer’s posting
Lead the design and implementation of a scalable Enterprise Data Warehouse (EDW)
Develop and maintain data pipelines (ETL/ELT) 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.
Define conceptual, logical, and physical data models to map out how different data entities relate to one another.
Establish standards for data quality, security, privacy, and compliance (e.g., GDPR, CCPA).
What you’ll bring
All qualificationsCore experience
- Proven experience delivering production-grade data pipelines using Python, SQL, and REST APIs.
- 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.
Preferred experience
- Hands-on experience with Azure cloud services, including administration tasks such as subscription management and Key Vault; familiarity with GCP is a plus.
Qualification wording
Proven experience delivering production-grade data pipelines using Python, SQL, and REST APIs.
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.
Hands-on experience with Azure cloud services, including administration tasks such as subscription management and Key Vault; familiarity with GCP is a plus.
Education & alternatives
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
Posting record
Report an errorOpen 4 monthsWe first saw this posting 125 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jul 2, 2026125 days ago
- Recorded sightings
- 46
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 125
Up longer than most. Similar jobs usually come down between day 5 and day 54.
From 10,704 similar postings that came down. Coming down is not always a hire.
Cognite - AI for Industry is hiring
7 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Data Engineer hiring is steady
- Takes jobs down at a usual pace
- 29% of open jobs were reposted
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Java
- Python
- SQL
- Azure
- Power BI
- Spark
- Terraform
- PySpark
Where the posting names them
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.
• 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.
• 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
• 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.
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.
• 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.
• 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.
• 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.
• 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
Your next step
Complete your application on job-boards.eu.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
What Cognite is: Relentless to 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.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
USA (Phoenix)
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.