We are seeking a Data Engineer to design, build, and scale Tenna Systems’ mission-critical data platform powering our RF and spectrum analytics across maritime, aerial, and space domains. This role focuses on developing cloud-native data infrastructure that transforms raw signal intelligence into reliable, real-time operational insight. The Data Engineer will work across batch and on-demand pipeline systems, schema architecture, and infrastructure-as-code tooling to support Tenna’s spectrum intelligence and resilience capabilities. The role includes building high-performance Spark pipelines on Databricks, shaping data contracts and type-safe platform services, and developing internal developer tooling that generates typed client libraries from a single source of truth across platforms and languages. This position requires strong end-to-end ownership across the full data lifecycle — from architecture and pipeline design through deployment, observability, and cost optimization — while collaborating closely with engineering, data science, and field teams to deliver resilient, production-grade systems used in operational environments. Qualifications- B.Sc. in Computer Science, Engineering, or equivalent practical experience (Required)- 5+ years of professional Backend/Data Engineering experience, including 3+ years in Data Engineering specifically- Production experience with Apache Spark and Delta Lake (or equivalent lakehouse formats: Iceberg, Hudi)- Strong SQL and Python, including solid data modeling, schema design, and performance tuning- Proven track record building large-scale, multi-tenant data pipelines and platform services- Pragmatic approach to cost/latency trade-offs, caching, partitioning strategy, and storage formats- AWS (or equivalent cloud provider) fluency, with Terraform/IaC experience and a GitOps mindset- Familiarity with Databricks (Unity Catalog, workflows, cluster tuning), geospatial data formats (H3, S2, Geohash), or internal developer tooling is a strong advantage