[Hiring] Principal Data Engineer @Gather AI

Role Description

As Principal Data Engineer, you'll architect Gather AI's data foundation from the ground up:

• Separate analytical workloads from live production traffic.
• Build a semantic layer so metrics are defined once and stay consistent everywhere.
• Link structured records to real drone imagery and video with full traceability.
• Prove the model end to end on Gather's drone product.
• Generalize the model so every new product extends the foundation instead of rebuilding it.
• Work as a Principal-level individual contributor with real influence across engineering, product, and leadership.

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 and leading an OLTP to OLAP transition.
• Deep expertise designing multi-layer transformation architectures and reusable frameworks.
• Expert SQL and dbt, hands-on ELT and orchestration, and large-scale or streaming data experience.
• Production experience on a major cloud (Azure preferred, AWS or GCP acceptable).
• Track record with data quality, security, governance, and 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 and reliable execution across data flows.
• Large-scale and distributed processing of high-volume batch data.
• Real-time and streaming ingestion that captures and processes event data as it arrives.
• Semantic and metrics-layer design that defines business metrics once and serves them consistently.
• Serving-layer optimization for fast, low-latency consumption through wide and flattened tables.
• Cloud data engineering and infrastructure automation that provisions, deploys, and operates the platform reproducibly.
• Data quality, observability, and lineage that ensure trust, freshness, and end-to-end traceability.
• Security, governance, and multi-tenancy including tenant isolation and access control.
• Multimodal data integration that links structured records to unstructured image and video.

Requirements

• Treats data as a product for internal consumers, not just a pipeline feeding dashboards.
• Comfortable making long-lead architecture calls with incomplete consensus.
• Strong cross-functional collaborator, working closely with integration/backend, ML, product, customer success teams, and internal analytics consumers.

Nice to Have

• Experience modeling structured data linked to unstructured or blob data such as images, video, or sensor files.
• Experience with feature stores, annotation pipelines, or 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.