> Markdown version of [/jobs/ext/3699645-staff-data-platform-engineer](https://www.wearedevelopers.com/jobs/ext/3699645-staff-data-platform-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Data Platform Engineer

- **Company:** Umbra Inc.
- **Location:** Santa Barbara, CA, United States
- **Experience:** Expert
- **Salary:** $185,000.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Data Architecture, Data Governance, Data Infrastructure, Data Transformation, Data Systems, Data Visualization, Data Warehousing, DevOps, GIS Applications, Apache Hadoop, Hadoop Distributed File System, Apache HBase, Identity and Access Management, Python (Programming Language), Machine Learning, Metadata Repositories, Power BI, Cloud Services, Prometheus, SQL Databases, Tableau (Software), Datadog, Data Storage Technologies, Grafana, Apache Spark, Data Layers, Information Technology, Data Analytics, Splunk, New Relic (SaaS), Software Version Control, Data Pipelines, Databricks
- **Published:** October 12, 2026
- **Apply:** https://www.juju.com/job/16_d9ae85941

## About the Role

* Bachelor's degree in computer science, data science, or a related field.
 * 15+ years of professional experience as a data engineer or in similar roles.
 * Strong proficiency in SQL and experience with data warehousing, lakehouse architecture, and analytics engineering concepts.
 * Proficiency in data pipeline development using Python and SQL, utilizing version control and CI/CD best practices.
 * Proficiency with analytics and visualization tools such as Omni Analytics, Tableau, Power BI, or similar.
 * Experience with Databricks, Apache Hadoop Ecosystem (HDFS, Spark, HBase, etc), or similar large-scale data processing and lakehouse platforms.
 * Experience with dbt or similar data transformation and modeling frameworks.
 * Experience with cloud platforms such as AWS, GCP, or Azure for building reliable data storage and processing.
 * Familiarity with monitoring and observability solutions such as Datadog, Grafana, Prometheus, New Relic, Splunk, or similar.
 * Effective communication skills, ability to work collaboratively in a team environment, and willingness to learn new skills and technology.

Desired Qualifications

 * Experience working in the aerospace industry.
 * Experience with mission scheduling software and/or schedule optimization.
 * Experience developing SAR image processing/formation applications.
 * Experience with Infrastructure-as-Code, DevOps, Identity and Access Management, and Developer Platforms.
 * Experience building custom GIS applications, STAC, or other imagery catalog APIs.
 * Experience with semantic layers, data catalogs, lineage, or data quality tooling.
 * Current security clearance or willingness and ability to acquire one.

## Description

We are seeking a Senior/Staff Data Platform Engineer to lead our data infrastructure architecture. The individual filling this position will collaborate with product owners and multidisciplinary engineering teams to design, develop, and maintain the data systems that support our autonomous satellite operations, analytics, and internal decision-making. They will play a key role in Umbra's efforts toward redefining how space radar data is consumed., * Design, build, and maintain scalable data pipelines and infrastructure to process, model, and analyze large volumes of satellite, operations, and business data

 * Develop and optimize data models, data warehouses, lakehouse patterns, and dbt transformations to support internal analytics, machine learning applications, and operational decision-making
 * Build and operate analytics and data platform capabilities using tools such as Databricks, dbt, Omni Analytics, and related cloud services
 * Collaborate with cross-functional teams to understand data requirements and ensure data quality, reliability, performance, and usability
 * Implement best practices for data governance, reliability, security, compliance, lineage, cost management, and observability