Sr. Data Engineer

Ursa Space Systems is seeking a Senior Data Engineer to shape the core data platform that powers advanced analytics and machine learning. This remote role centers on architecting, scaling, and sustaining dependable data infrastructure, building robust pipelines, and managing cloud data warehouses, all while enabling secure, fine-grained access to a scalable geospatial reservoir and data lake. You will lead governance and engineering benchmarks to ensure high availability and operational excellence across the organization.

Responsibilities

• Define and evolve the data engineering roadmap to align with business strategy and security standards.
• Provide architectural leadership for cross-team data initiatives, ensuring solutions are scalable, secure, resilient, and maintainable.
• Guide data platform and vendor evaluations, balancing build versus buy decisions with enterprise direction.
• Develop and promote standards for lakehouse architecture, ELT/ETL, data modeling, CI/CD, observability, and governance.
• Anticipate technology impacts across applications, data, integrations, and infrastructure, guiding teams through informed trade-offs and evaluating new technology.
• Engage in hands-on delivery and implementation using modern data platforms, processes, and practices.
• Provide technical direction for large or multi-team deliveries, applying modern data engineering and DevSecOps practices.
• Conduct architectural and technical reviews of designs, code, and delivery approaches to improve quality and consistency.
• Champion automation, observability, and operational excellence to keep platforms reliable, performant, and cost-effective.
• Pilot emerging technologies and guide their integration into stable enterprise capabilities when appropriate.
• Drive continuous improvement of engineering practices, tooling, automation, and operational processes.
• Occasional nights and weekends may be required based on company needs.
• Additional duties as assigned.

Requirements

• Bachelor’s degree or equivalent experience; advanced degree preferred; minimum of 10+ years in enterprise data engineering.
• Mastery-level knowledge in data engineering with deep experience in lakehouse architecture, distributed processing, cloud data warehousing, data transformation frameworks, or data governance.
• Proven ability to craft implementation plans for complex, enterprise-scale data platforms and pipelines supporting analytics, reporting, AI/ML, and operational decisions.
• Track record of developing standards, processes, and operational plans that enhance stability, resilience, security, and performance of critical data platforms.
• Deep expertise with cloud data platforms including Azure Data Services, Databricks, Snowflake, and DBT Cloud.
• Strong foundation in enterprise data architecture and secure, scalable technology solutions.
• Advanced experience with CI/CD for data workloads, infrastructure as code, cloud-native operations, and modern version control.
• Proficiency with programming tools such as Azure Data Factory, Fivetran, Databricks Notebook, DBT Cloud, ETL/ELT frameworks, and languages like Python, SQL, Spark (PySpark/Scala), plus scripting common in cloud data environments.
• Proven success leading large-scale data modernization, including migration from legacy warehouses to modern cloud platforms.
• Experience managing and reviewing vendors or offshore teams to ensure alignment with enterprise standards and long-term sustainability.
• Excellent communication and influencing skills, with the ability to translate complex concepts to senior leadership, technical teams, and cross-functional partners.
• Ability to enable AI through data, understanding AI use cases and the data architecture, quality, governance, lineage, and scalability requirements needed for AI initiatives.
• Strong analytical and problem-solving abilities with a commitment to operational excellence and continuous learning.
• Mentorship potential to guide junior engineers and build capability across the data engineering group.

Technologies

• Azure Data Services
• Databricks
• Snowflake
• DBT Cloud
• Azure Data Factory
• Fivetran
• Databricks Notebook
• Python, SQL, PySpark, Scala
• ETL/ELT frameworks

Benefits

• Competitive compensation
• Discretionary PTO and flexible scheduling
• Stock options
• 401(k) match
• Medical, dental, and vision coverage for you and dependents
• FSA and HSA plans
• Employer-paid life insurance
• Employer-paid LTD and STD for parental and family care
• 11 paid holidays
• Employee resource groups
• Educational assistance program
• Professional development opportunities
• And more

Location & Travel

Remote or hybrid arrangements are supported. Occasional attendance at mandatory Ursa Space meetings at the headquarters in Ithaca, NY is required, typically 2–3 times per year.

Compensation

Salary: USD 150,000 - 200,000 per year, commensurate with skills and experience.

Company Values

• Use the team
• Figure it out and own it
• Aim for elegant simplicity
• Empower diversity and inclusivity
• Do the right thing
• Be scrappy