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Senior Data Engineer

LinkedIn Varda Space Industries El Segundo, CA
Mid-Senior level Posted April 2, 2026 Job link
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Requirements
  • Provide technical leadership and mentoring to application engineers and business end users.
  • Experience interfacing with engineering and manufacturing groups to understand system designs and translations to data needs.
  • Experience conducting or contributing to platform trade studies or build-vs-buy evaluations for data infrastructure.
  • Experience supporting AI/ML pipelines including feature stores, training data pipelines, or model monitoring infrastructure.
  • Experience in a start-up or similar high growth environment.
  • Familiarity with workflow orchestration tools (ex: Airflow).
  • Exposure to aerospace, defense, or pharmaceutical data environments.
  • Experience contributing to or leading a data platform migration or modernization effort.
  • Experience working with ERP systems deployed in a design development environment.
  • Exposure to Infrastructure as Code for cloud resource provisioning (e.g., Terraform).
  • Relevant platform or tooling certifications (ex: dbt Certified Developer, cloud data platform certifications).
  • 7+ years of experience in enterprise integration or data engineering roles (advanced degrees count towards years of experience).
  • Deep hands-on experience with cloud-scale data warehouse or Lakehouse platforms (ex: Snowflake, Databricks).
  • Includes performance tuning, cost governance, and data sharing patterns at scale.
  • Strong experience building and managing a modern transformation layer in production.
  • Includes project structure, testing strategy, and metrics/semantic layer (ex: dbt).
  • Fluency in a general-purpose programming language for pipeline development, scripting, and data transformation logic (ex: SQL, Python, R, Java).
  • Experience integrating data from enterprise source systems such as ERP and CRM.
  • Includes handling schema complexity, API connectivity, and change management (ex: Deltek, SAP, Salesforce).
  • Strong data modeling fundamentals with the ability to evaluate and apply the right approach based on the use case.
  • Solid source control and deployment discipline.
  • Branching strategies, peer review workflows, and CI/CD tooling treated as non-negotiable engineering standards.
  • Proven ability to write efficient, well-documented, testable code and implement data quality testing strategies at the model, pipeline, and source level.
  • Includes familiarity with data observability tooling (ex: Metaplane, Monte Carlo).
  • Deep knowledge of software architecture principles, including event-driven and service-oriented architectures (EDA/SOA) and ELT workflows.
  • Strong understanding of data warehousing, ETL processes, connecting enterprise systems, and data modeling.
  • Capability to gather business requirements from stakeholders and take a project from initial concept to finished product.
  • Ability to work with end users to rapidly iterate on prototype applications by solving end user issues.
  • Ability to translate technical concepts to non-technical audiences for stakeholders internal and external to the organization.
  • Strong interpersonal and communication skills.
  • Ability to lead and/or work well in cross-functional teams.
  • Ability to lawfully access information and technology that is subject to US export controls.
Preferred Skills
  • Graduate degree in Computer Science, Information Systems, or related fields.
  • Experience interfacing with engineering and manufacturing groups to understand system designs and translations to data needs.
  • Experience conducting or contributing to platform trade studies or build-vs-buy evaluations for data infrastructure.
  • Experience supporting AI/ML pipelines including feature stores, training data pipelines, or model monitoring infrastructure.
  • Experience in a start-up or similar high growth environment.
  • Familiarity with workflow orchestration tools (ex: Airflow).
  • Exposure to aerospace, defense, or pharmaceutical data environments.
  • Experience contributing to or leading a data platform migration or modernization effort.
  • Experience working with ERP systems deployed in a design development environment.
  • Exposure to Infrastructure as Code for cloud resource provisioning (e.g., Terraform).
  • Relevant platform or tooling certifications (ex: dbt Certified Developer, cloud data platform certifications).
  • Branching strategies, peer review workflows, and CI/CD tooling treated as non-negotiable engineering standards.
  • Strong understanding of data warehousing, ETL processes, connecting enterprise systems, and data modeling.
  • Capability to gather business requirements from stakeholders and take a project from initial concept to finished product.
  • Ability to work with end users to rapidly iterate on prototype applications by solving end user issues.
Education
  • (Not required) – Graduate degree in Computer Science, Information Systems, or related fields.
  • (Not required) – Bachelor's degree in Computer Science, Information Systems, or related fields.