Software Engineer, Facilities Pipeline
Build and own the facilities data pipeline for AI data center telemetry, including ingestion from industrial protocols (BACnet, Modbus, OPC UA), data quality tooling, and serving clean APIs/datasets for dashboards, controls, and ML. Requires production data pipeline experience with on-call ownership, industrial protocol integration, and full-stack debugging.
About the job
Build the facilities data pipeline
- Ingestion, transformation, and serving of telemetry from every site.
- Ship the connectors that speak the field's languages: BACnet, Modbus, OPC UA, and vendor APIs, reliably.
- Own data quality in code: validation, gap detection, and backfill tooling.
- Serve the consumers: clean APIs and datasets for dashboards, controls, and ML.
Requirements
- Shipped production data pipelines and owned them on call.
- Integrated with industrial protocols or ugly vendor APIs and made them reliable.
- Test data code properly: correctness, latency, and gaps.
- Debug across the stack, from a flatlined sensor to a slow query.
- Work fast with modern tooling and AI-assisted development.
Nice-to-Haves
- Time-series systems.
- Go, Python, or TypeScript.
- Industrial and IoT data.
- Grafana ecosystems.
Skills
Data Pipelines, Bacnet, Modbus, Opc Ua, Industrial Protocols, Vendor Apis, Data Validation, Time-Series Databases, Go, Python, TypeScript, Grafana, Iot Data
Similar jobs
Data Engineering jobs
Fluidstack
Austin, TXBuild and own production data pipelines, knowledge graph data models, and structured datasets from messy sources (PDFs, spreadsheets, telemetry) to power internal tools, dashboards, and ML models at a frontier AI compute infrastructure company. Requires experience operating depended-on pipelines, schema modeling, data quality engineering, and unstructured data extraction.
Thinking Machines Lab
San Francisco, CA
Own end-to-end data sourcing and vendor operations that help researchers train and evaluate frontier AI models. The role requires strong judgment, communication, problem-solving, and comfort managing ambiguous, fast-changing projects.
OpenAI
Mountain View, CABuild and operate scalable monetization data platforms, pipelines, models, and quality systems spanning product, financial, and operational data. The role partners with Product Engineering, Finance, Accounting, Analytics, and GTM teams to deliver reliable, observable data products.
The Voleon Group
New York, NYBuild and evolve reliable analytics infrastructure, pipelines, schemas, and foundational datasets supporting quantitative research across strategies. The role requires strong Python and SQL skills, distributed data-platform experience, and ownership of observability, performance, and reproducibility.
Anthropic
San Francisco, CABuild and govern quote-to-cash data models and products integrating Salesforce, CPQ, billing, and finance systems. The role requires 5+ years of data engineering experience, strong SQL and Python skills, and expertise in self-service analytics for GTM teams.