Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,239 postings in the last year. Stated ranges, not salaries paid.
Senior Data Platform Engineer
Madison, Wisconsin, United States; Pasadena, California, United States; San Diego, California, United States; Verona, Wisconsin, United States
Live, first seen by us 22 days ago- Pay
Multiple pay statements — pay source
Wisconsin pay range $155,000—$175,000 USD California pay range
California pay range $175,000—$190,000 USD Arrowhead provides competitive salaries and an excellent benefit package.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Employer’s visa record
- 6 H-1B petitions approved in fiscal 2024 and 2025For the employer as a whole. This posting doesn’t say whether the role is sponsored. US Citizenship and Immigration Services.
What you’ll work on
Full postingDesign, build and manage Databricks workspaces, clusters, Unity Catalog and SQL warehouses
Develop Terraform modules and pipelines to provision and version-control Databricks infrastructure
Build ingestion pipelines from internal systems and third-party providers into the lakehouse
Maintain medallion (bronze/silver/gold) Delta Lake layers with data quality and governance
Build and support Genie dashboards with business and analytics users
From the employer’s posting
Design, build, and manage Databricks environments (workspaces, clusters, Unity Catalog, SQL warehouses)
Develop and maintain Terraform modules and pipelines to provision, configure, and version-control all Databricks infrastructure
Design and build data ingestion pipelines to bring in data from internal systems and external third-party data providers
Architect and maintain medallion (bronze/silver/gold) data layers using Delta Lake, ensuring data quality, lineage, and governance via Unity Catalog
Partner with business and analytics end users to design, build, and support Genie dashboards
What you’ll bring
All qualificationsCore experience
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience
- Experience with Databricks Genie and building natural-language / self-service analytics experiences for business users
- 5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses)
- Experience integrating data from external data providers or vendor APIs at enterprise scale
- Demonstrated experience managing Databricks infrastructure as code using Terraform
- Familiarity with CI/CD tooling (e.g., GitHub Actions, Azure DevOps, GitLab CI) for automated deployment of Terraform-managed infrastructure
Qualification wording
Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience
Experience with Databricks Genie and building natural-language / self-service analytics experiences for business users
5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses)
Experience integrating data from external data providers or vendor APIs at enterprise scale
Demonstrated experience managing Databricks infrastructure as code using Terraform
Familiarity with CI/CD tooling (e.g., GitHub Actions, Azure DevOps, GitLab CI) for automated deployment of Terraform-managed infrastructure
Education & alternatives
Requirements - Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience - 5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses)
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 20, 202622 days ago
- Recorded sightings
- 24
- Last seen by us
- Nov 12, 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 22
Similar jobs usually come down between day 6 and day 55.
From 13,324 similar postings that came down. Coming down is not always a hire.
Arrowhead Pharmaceuticals is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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.
- Python
- SQL
- AWS
- Azure
- Databricks
- dbt
- Delta Lake
- Terraform
- Airflow
Where the posting names them
- Demonstrated experience managing Databricks infrastructure as code using Terraform - Strong proficiency in Python and SQL for building and optimizing data pipelines - Experience designing and building data ingestion pipelines from diverse internal and external data sources (APIs, SFTP, third-party vendor feeds, streaming)
Responsibilities - Design, build, and manage Databricks environments (workspaces, clusters, Unity Catalog, SQL warehouses) supporting enterprise analytics and data science workloads - Develop and maintain Terraform modules and pipelines to provision, configure, and version-control all Databricks infrastructure and related cloud resources
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience - 5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses) - Demonstrated experience managing Databricks infrastructure as code using Terraform
- Experience designing and building data ingestion pipelines from diverse internal and external data sources (APIs, SFTP, third-party vendor feeds, streaming) - Working knowledge of cloud platforms (AWS, Azure ) and associated data/storage services - Experience supporting business intelligence or natural-language dashboarding tools (e.g., Databricks Genie )
- Experience integrating data from external data providers or vendor APIs at enterprise scale - Familiarity with CI/CD tooling (e.g., GitHub Actions, Azure DevOps, GitLab CI) for automated deployment of Terraform-managed infrastructure - Experience with data orchestration tools (e.g., Databricks Workflows, Airflow, dbt)
The Position The Senior Data Platform Engineer is responsible for designing, building, and managing the organization's Databricks environments, with end-to-end ownership of the data platform's infrastructure, security, and performance. This role leads the ingestion of data from internal systems and external third-party providers into the lakehouse, partners with business and analytics stakeholders to build and support Genie dashboards, and manages the Databricks platform (workspaces, clusters, Unity Catalog, jobs) as infrastructure-as-code using Terraform. The ideal candidate has hands-on experience administering Databricks in production, writing Terraform for infrastructure changes, and building data pipelines that hold up at enterprise scale. Responsibilities
- Design, build, and manage Databricks environments (workspaces, clusters, Unity Catalog, SQL warehouses) supporting enterprise analytics and data science workloads - Develop and maintain Terraform modules and pipelines to provision, configure, and version-control all Databricks infrastructure and related cloud resources - Design and build data ingestion pipelines to bring in data from internal systems and external third-party data providers (APIs, SFTP, batch files, streaming sources) into the lakehouse.
- 5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses) - Demonstrated experience managing Databricks infrastructure as code using Terraform - Strong proficiency in Python and SQL for building and optimizing data pipelines
- Working knowledge of cloud platforms (AWS, Azure ) and associated data/storage services - Experience supporting business intelligence or natural-language dashboarding tools (e.g., Databricks Genie ) - Experience implementing data governance, security, and access controls in Databricks (e.g., Unity Catalog permissions, row/column-level security, service principals, secrets management)
- Experience supporting business intelligence or natural-language dashboarding tools (e.g., Databricks Genie ) - Experience implementing data governance, security, and access controls in Databricks (e.g., Unity Catalog permissions, row/column-level security, service principals, secrets management) - Ability to explain pipeline and dashboard design decisions to non-technical stakeholders, e.g., when scoping Genie dashboard requirements with business users
Preferred - Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Associate/Professional Platform Administrator) - Experience with Databricks Genie and building natural-language / self-service analytics experiences for business users
- Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Associate/Professional Platform Administrator) - Experience with Databricks Genie and building natural-language / self-service analytics experiences for business users - Experience integrating data from external data providers or vendor APIs at enterprise scale
- Familiarity with CI/CD tooling (e.g., GitHub Actions, Azure DevOps, GitLab CI) for automated deployment of Terraform-managed infrastructure - Experience with data orchestration tools (e.g., Databricks Workflows, Airflow, dbt) - Experience building and supporting agentic workloads on Databricks, including managing model/tool access and governance via the Unity Catalog AI Gateway
- Experience with data orchestration tools (e.g., Databricks Workflows, Airflow, dbt) - Experience building and supporting agentic workloads on Databricks, including managing model/tool access and governance via the Unity Catalog AI Gateway - Expertise in pharma or pharma-related data (e.g., clinical, R&D, regulatory, or commercial pharma data) and the compliance considerations that come with it
- Design and build data ingestion pipelines to bring in data from internal systems and external third-party data providers (APIs, SFTP, batch files, streaming sources) into the lakehouse. - Architect and maintain medallion (bronze/silver/gold) data layers using Delta Lake, ensuring data quality, lineage, and governance via Unity Catalog - Partner with business and analytics end users to design, build, and support Genie dashboards and enable self-service, natural-language data exploration
- Implement platform security, access controls, and partner with data stewards. - Work with data engineers, analysts, data scientists, AI engineers, and cloud DevOps engineers to build and maintain CI/CD pipelines, automated tests, and Terraform infrastructure-as-code for the data platform - Document platform architecture, ingestion pipelines, and operational runbooks
Your next step
Complete your application on arrowheadpharma.com. 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 Arrowhead Pharmaceuticals
- People
- About 711 in 2025, up 17% from the year before.Annual report (SEC Form 10-K)
- Company
- Listed as ARWR.
Demand for Data Engineer roles
New Data Engineer postings at the employers we follow are up 7% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
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
Arrowhead Pharmaceuticals, Inc. (Nasdaq ARWR) is a commercial stage biopharmaceutical company that develops medicines that treat intractable diseases by silencing the genes that cause them. Using a broad portfolio of RNA chemistries and efficient modes of delivery, Arrowhead therapies trigger the RNA interference mechanism to induce rapid, deep, and durable knockdown of target genes. RNA interference, or RNAi, is a mechanism present in living cells that inhibits the expression of a specific gene, thereby affecting the production of a specific protein. Arrowhead’s RNAi-based therapeutics leverage this natural pathway of gene silencing.
Arrowhead is focused on developing innovative drugs for diseases with a genetic basis, typically characterized by the overproduction of one or more proteins that are involved with disease. The depth and versatility of our RNAi technologies enables us to potentially address conditions in virtually any therapeutic area and pursue disease targets that are not otherwise addressable by small molecules and biologics. Arrowhead is leading the field in bringing the promise of RNAi to address diseases outside of the liver, and our clinical pipeline includes disease targets in the liver and lung with a promising pipeline of preclinical candidates.
Arrowhead’s corporate headquarters is in Pasadena, CA with research and development teams in Madison, WI & San Diego, CA, and a state of the art manufacturing facility in Verona, WI. Our employees are nimble, science-driven innovators who are collaborating to bring new therapies to patients in need.
The Position
The Senior Data Platform Engineer is responsible for designing, building, and managing the organization's Databricks environments, with end-to-end ownership of the data platform's infrastructure, security, and performance. This role leads the ingestion of data from internal systems and external third-party providers into the lakehouse, partners with business and analytics stakeholders to build and support Genie dashboards, and manages the Databricks platform (workspaces, clusters, Unity Catalog, jobs) as infrastructure-as-code using Terraform. The ideal candidate has hands-on experience administering Databricks in production, writing Terraform for infrastructure changes, and building data pipelines that hold up at enterprise scale.
Responsibilities
- Design, build, and manage Databricks environments (workspaces, clusters, Unity Catalog, SQL warehouses) supporting enterprise analytics and data science workloads
- Develop and maintain Terraform modules and pipelines to provision, configure, and version-control all Databricks infrastructure and related cloud resources
- Design and build data ingestion pipelines to bring in data from internal systems and external third-party data providers (APIs, SFTP, batch files, streaming sources) into the lakehouse.
- Architect and maintain medallion (bronze/silver/gold) data layers using Delta Lake, ensuring data quality, lineage, and governance via Unity Catalog
- Partner with business and analytics end users to design, build, and support Genie dashboards and enable self-service, natural-language data exploration
- Implement platform security, access controls, and partner with data stewards.
- Work with data engineers, analysts, data scientists, AI engineers, and cloud DevOps engineers to build and maintain CI/CD pipelines, automated tests, and Terraform infrastructure-as-code for the data platform
- Document platform architecture, ingestion pipelines, and operational runbooks
- Assist AI engineers by building and maintaining MCP (Model Context Protocol) connectors and other data/tool integrations that power agentic workflows
Requirements
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, or related field, or equivalent practical experience
- 5+ years of experience in data engineering or platform engineering roles, including extensive hands-on experience administering and building on Databricks (clusters, jobs, Unity Catalog, Delta Lake, SQL warehouses)
- Demonstrated experience managing Databricks infrastructure as code using Terraform
- Strong proficiency in Python and SQL for building and optimizing data pipelines
- Experience designing and building data ingestion pipelines from diverse internal and external data sources (APIs, SFTP, third-party vendor feeds, streaming)
- Working knowledge of cloud platforms (AWS, Azure ) and associated data/storage services
- Experience supporting business intelligence or natural-language dashboarding tools (e.g., Databricks Genie )
- Experience implementing data governance, security, and access controls in Databricks (e.g., Unity Catalog permissions, row/column-level security, service principals, secrets management)
- Ability to explain pipeline and dashboard design decisions to non-technical stakeholders, e.g., when scoping Genie dashboard requirements with business users
Preferred
- Databricks certifications (e.g., Databricks Certified Data Engineer Professional, Databricks Certified Associate/Professional Platform Administrator)
- Experience with Databricks Genie and building natural-language / self-service analytics experiences for business users
- Experience integrating data from external data providers or vendor APIs at enterprise scale
- Familiarity with CI/CD tooling (e.g., GitHub Actions, Azure DevOps, GitLab CI) for automated deployment of Terraform-managed infrastructure
- Experience with data orchestration tools (e.g., Databricks Workflows, Airflow, dbt)
- Experience building and supporting agentic workloads on Databricks, including managing model/tool access and governance via the Unity Catalog AI Gateway
- Expertise in pharma or pharma-related data (e.g., clinical, R&D, regulatory, or commercial pharma data) and the compliance considerations that come with it
Wisconsin pay range
$155,000—$175,000 USD
California pay range
$175,000—$190,000 USD
Arrowhead provides competitive salaries and an excellent benefit package.
Candidates must have current, valid authorization to work in the country where this role is located.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Wisconsin pay range $155,000—$175,000 USD California pay range
More source context
California pay range $175,000—$190,000 USD Arrowhead provides competitive salaries and an excellent benefit package.
- Location & working pattern
Madison, Wisconsin, United States; Pasadena, California, United States; San Diego, California, United States; Verona, Wisconsin, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.