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About the Role
We are seeking a seasoned Senior Data Engineer to architect, enhance, and sustain our primary data infrastructure. You will be responsible for creating dependable pipelines, overseeing cloud-based data warehouses, and guaranteeing high-availability data access for machine learning and analytics units. This role involves architecting a scalable data reservoir for extensive geospatial datasets and establishing a secure data lake architecture with role-based access controls. As a technical authority, you will define engineering benchmarks, mentor engineers, and bolster data platform capabilities, turning challenges into viable data strategies and scalable solutions.
Responsibilities
- Define and evolve data engineering technology roadmaps aligned to business strategies, enterprise architecture, and information security standards.
- Provide architectural leadership on complex, cross-team data initiatives, ensuring scalable, secure, resilient, and maintainable solutions.
- Lead data platform and vendor evaluations, guiding build vs. buy decisions and ensuring consistency with enterprise technical direction.
- Develop and promote data engineering standards for lakehouse architecture, ELT/ETL frameworks, data modeling, CI/CD, observability, and governance.
- Anticipate technology impacts across applications, data, integrations, and infrastructure, guiding teams through informed trade-off decisions.
- Perform day-to-day hands-on execution and implementation of solutions using modern data platforms, initiatives, processes, and practices.
- Provide technical direction for large or multi-team delivery efforts, ensuring application of modern data engineering and DevSecOps practices.
- Conduct architectural and technical reviews of solution designs, code, and delivery approaches to raise quality and consistency.
- Champion automation, observability, and operational excellence to ensure platforms remain reliable, performant, and cost-effective.
- Pilot emerging technologies and guide their adoption into stable enterprise capabilities.
- Drive continuous improvement of engineering practices, tooling, automation, and operational processes.
- May be required to work occasional nights and weekends.
- Perform other duties as assigned.
Requirements
- Bachelor’s degree or equivalent experience, typically requiring an advanced degree or equivalent experience.
- Minimum of 10+ years of relevant data engineering experience in enterprise environments.
- Mastery-level knowledge of the data engineering field and modern data platform technology delivery.
- Deep experience in one or more key domains such as lakehouse architecture, distributed data processing, cloud data warehousing, data transformation frameworks, or data governance.
- Demonstrated ability to build and complete implementation plans for complex, enterprise-scale data platforms and pipelines supporting analytics, reporting, AI/ML, and operational decision-making.
- Proven experience developing and implementing standards, processes, and operational plans that improve stability, resilience, security, and performance of critical data platforms.
- Deep expertise with cloud-based data platforms including Azure Data services, Databricks, Snowflake, and DBT cloud.
- Strong foundation in enterprise data architecture fields and the development of secure, scalable, aligned technology solutions.
- Advanced experience with CI/CD pipelines for data workloads, infrastructure as code, cloud-native operational models, and modern version control strategies.
- Strong proficiency in programming using data processing tools like Azure Data Factory, Fivetran, Databricks notebook, DBT cloud, ETL/ELT frameworks.
- Proficiency in programming languages such as Python, SQL, Spark (PySpark/Scala), and scripting languages common to cloud data environments.
- Demonstrated success leading large-scale and complex data modernization initiatives, including migration from legacy data warehouses to modern cloud-based data platforms.
- Experience managing and reviewing vendors or offshore engineering work to ensure alignment with enterprise data standards, architecture principles, and long-term sustainability.
- Excellent communication and influencing skills, with the ability to translate complex data architecture concepts into actionable recommendations for various stakeholders.
- Demonstrated ability to enable AI through data, with a strong understanding of AI use cases and the necessary data architecture, quality, governance, lineage, and scalability requirements.
- Strong analytical and problem-solving abilities, demonstrating dedication to operational excellence, continuous learning, and improving data engineering practices.
- May mentor, review, and delegate work to more junior engineers.
Skills
- Azure Data services
- Databricks
- Snowflake
- DBT cloud
- Azure Data Factory
- Fivetran
- Databricks notebook
- ETL/ELT frameworks
- Python
- SQL
- Spark (PySpark/Scala)
- CI/CD pipelines
- Infrastructure as code
- Cloud-native operational models
- Version control strategies
- Data modeling
- Observability
- Data governance
- Geospatial datasets
Location
- Ithaca, NY
- Remote (United States)
Work Type
- Remote
- Full-time
Experience Level
- Senior
- 10+ years
Education Level
- Bachelor's degree or equivalent experience
- Advanced degree or equivalent experience
Salary/Compensations
- $150,000 - $200,000
Benefits
- Competitive Compensation
- Discretionary PTO & Flexible Scheduling
- Stock Options
- 401(k) Match
- Medical, Dental and Vision Coverage
- FSA & HSA Plans
- Employer-paid Life Insurance
- Employer-paid LTD and STD
- 11 Paid Holidays
- Employee Resource Groups
- Educational Assistance Program
- Professional Development Opportunities
About the Company
- Ursa Space Systems is a leader in geospatial intelligence, providing data and analytics derived from satellite imagery and other sources.
- Company Values: Use the team, Figure it out and own it, Aim for elegant simplicity, Empower diversity & inclusivity, Do the right thing, Be scrappy.
Equal Opportunity
- Ursa Space Systems is an equal opportunity employer.