Data Engineer San Francisco

R-Zero offers smart building technology that delivers real-time occupancy and energy insights, which ultimately helps buildings reduce energy costs, improve net operating income and increase asset value. R-Zero’s occupancy‑based demand control ventilation solutions include IAQ and comfort monitoring, high‑efficiency HVAC filtration, space utilization sensors, occupancy‑based building controls, and real‑estate performance analytics. R-Zero’s intuitive, secure and scalable platform enables owners, operators, and their tenants to cut building operating expenses and carbon emissions, with zero upfront costs.

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About the Role

R‑Zero’s smart building technology is at an inflection point. Our ODCV (Occupancy‑Based Demand Control Ventilation) implementations deliver real, measurable energy savings for commercial buildings—and demand is outpacing our ability to deliver. Our data infrastructure is straining to keep up with the pace of new projects.

We’re looking for a Staff Data Engineer to define and build the data architecture that will power R‑Zero’s next phase of growth. You’ll own the technical vision for how we handle millions of IoT data points daily, mentor engineers, and make decisions that shape our platform for years to come.

We need someone who can think strategically about data architecture while still getting their hands dirty when it matters.

As our Staff Data Engineer, you’ll be the technical leader for all things data. You’ll design the systems that transform how we handle IoT and building management system (BMS) data—from manual, project‑by‑project processes to automated, scalable pipelines that support 15‑20+ simultaneous implementations right off the bat and scale for future data products. You’ll partner with engineering leadership to set technical direction, influence product roadmap decisions, and build the foundation for AI‑driven building optimization.

• Define the data architecture strategy for R‑Zero’s IoT platform, making build vs. buy decisions and selecting technologies that will scale with our growth.
• Design a real‑time data infrastructure capable of ingesting thousands of data points per minute from diverse BMS protocols (BACnet, Modbus, Lon Works)
• Architect ML‑ready data pipelines that will power predictive energy models, anomaly detection, and automated optimization—laying the groundwork for AI capabilities
• Establish data quality frameworks, monitoring standards, and observability practices to catch issues in hours rather than weeks.

• Partner with engineering leadership to align data infrastructure investments with business priorities and product roadmap
• Drive technical decisions across teams, providing guidance on data modeling, pipeline design, and integration patterns.
• Mentor engineers on data engineering best practices, conduct design reviews, and raise the technical bar across the organization.
• Translate complex technical concepts for non‑technical stakeholders, helping leadership understand tradeoffs and make informed decisions.

• 8+ years of data engineering experience, with at least 2 years in a staff‑level role
• A track record of designing and implementing data architectures that scaled—you’ve made technology choices you’d make again
• Deep expertise in data orchestration (Airflow, dbt, Prefect), streaming systems, and time‑series databases
• Experience building data platforms that support ML/AI workloads—you understand what data scientists need to be productive
• Strong opinions on data modeling, loosely held—you can articulate tradeoffs and change your mind with new information
• The communication skills to influence without authority and build consensus across engineering, product, and leadership

• Experience with IoT data pipelines or building management systems
• Background building data infrastructure at a growth‑stage company (you’ve seen what breaks at scale)
• Experience with real‑time streaming architectures (Kafka, Kinesis, Flink)
• Passion for sustainability and energy efficiency
• Experience with CI/CD pipelines for automated data processing.

We’re a small, collaborative team…