Varda Space Industries
Data Engineer
About this role
Varda seeks a Data Engineer to build and maintain ELT pipelines, data storage solutions, and quality frameworks that support enterprise operations across regulated aerospace and pharmaceutical manufacturing. You'll collaborate cross-functionally to design scalable data architectures, enable AI/ML workflows, and ensure compliance with FDA, ITAR, and DCAA requirements.
What you'll do
- Build and maintain ELT pipelines ingesting data from ERP, CRM, PLM, QMS, and other enterprise systems
- Establish data quality frameworks, lineage tracking, and pipeline observability with SLA monitoring and alerting
- Design feature pipelines and governed knowledge layers to support AI/ML workflows
- Assist with data storage design including partitioning strategies and ecosystem interoperability
- Translate business requirements into technical specifications working with engineers and stakeholders
- Implement modern development practices including source control, CI/CD, and automated testing
What they're looking for
- ELT/ETL pipeline development
- Cloud data warehouse platforms (Snowflake, Databricks)
- SQL and relational database design
- Python or similar general-purpose programming language
- Data transformation tools (dbt)
- Git and CI/CD automation
- Data modeling (star schema, dimensional modeling)
- Enterprise systems (ERP, CRM, PLM, QMS)
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Varda Space Industries
Varda Space Industries builds commercial spacecraft and orbital manufacturing systems for missions in low Earth orbit, including reentry capsules and satellite buses. The company is hiring mission operations engineers, software engineers (ground segment, flight, and embedded), and manufacturing engineers to develop mission-critical systems, operational infrastructure, and scalable production capabilities.
- Website
- varda.com
Likely interview questions
- Describe your experience building ELT pipelines from enterprise systems like ERP or CRM—what tools and approaches did you use?
- How have you implemented data quality frameworks or SLA monitoring in production environments?