Principal Data Engineer
Remote
Job Summary
Architect a greenfield, multi-layer data warehouse separating analytical workloads from production OLTP traffic, and deliver a governed, self-service access layer for internal consumers. Build a semantic and metrics layer defining business metrics once in code to ensure consistency across dashboards and products. Own data quality with 99%+ availability SLAs, 100% traceability, and zero cross-tenant leakage while designing tenant isolation and row-level RBAC to scale toward hundreds of tenants. Prove the foundation end-to-end on the drone product, linking structured records to unstructured imagery and video with full traceability, then generalize it so new products extend the model instead of rebuilding. Stand up a data catalog and lineage layer using Purview or DataHub to enable consumers to find data and trace lineage.
Required Qualifications
- 10+ years in data engineering
- 3+ years architecting data platforms for data products, analytics, or AI-driven products
- Proven experience building a greenfield data warehouse
- Proven experience leading an OLTP to OLAP transition
- Deep expertise designing multi-layer transformation architectures
- Expert SQL
- Expert dbt
- hands-on ELT
- hands-on orchestration
- large-scale or streaming data experience
- Production experience on a major cloud
- Azure preferred
- AWS or GCP acceptable
- infrastructure as code
- CI/CD
- Track record with data quality
- Track record with security
- Track record with governance
- Track record with multi-tenancy in production environments
- Data transformation and modeling that turns raw multi-source data into refined, serving-ready datasets
- Pipeline orchestration and workflow automation for scheduling
- Pipeline orchestration and workflow automation for dependency management
- Pipeline orchestration and workflow automation for reliable execution
- Large-scale and distributed processing of high-volume batch data
- Real-time and streaming ingestion
- Real-time and streaming ingestion that captures and processes event data as it arrives
- Semantic and metrics-layer design that defines business metrics once
- Serving-layer optimization for fast, low-latency consumption
- Cloud data engineering and infrastructure automation that provisions, deploys, and operates the platform reproducibly
- cloud-native
- infrastructure as code
- CI/CD
- Data quality, observability, and lineage
- Security, governance, and multi-tenancy including tenant isolation
- Security, governance, and multi-tenancy including access control
- Security, governance, and multi-tenancy including resiliency
- Multimodal data integration that links structured records to unstructured image and video
- Multimodal data integration that links structured records to unstructured image and video (drone captures)
Desired Qualifications
- Experience modeling structured data linked to unstructured or blob data such as images, video, or sensor files
- Experience with feature stores
- Experience with annotation pipelines
- Experience with ML data infrastructure supporting computer vision products
- IoT, edge, or device-telemetry background
- BI or presentation-layer and dashboard design experience
- Warehousing, logistics, or supply-chain domain knowledge
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