Senior Data Engineer

About Us

Chorus is a suite of orchestration tools and services transforming how you make, move, and manage your assets. It’s an AI startup that recently spun out of Alphabet’s Moonshot Factory. Our mission is to transform how the world’s goods are made, moved, and managed. We stream data from our customers’ physical assets into advanced applications that show them what’s happening now, what’s likely to happen next, and—most importantly—what to do about it. We don’t sell sensors or raw data; we sell solutions to real business problems. Our customers rely on us to turn streams of IoT data into the intelligence that runs their operations. We’re a fun, supportive, and sharp team building the data refinery that makes this possible. If you want to work at the intersection of AI, IoT, and real-world problem-solving, this is the place.

The Role

We’re looking for a Senior Data Engineer to build the data infrastructure that powers customer-facing applications. Our Data Scientists design applications that solve operational problems; you’ll build the performant, cost-efficient data backends that make them possible.

Our platform processes high-volume, high-velocity IoT streams from physical assets—millions of sensor readings flowing into BigQuery, feeding real-time applications that can’t afford to be slow or expensive. You’ll design data models, optimize pipelines, build APIs, and obsess over the tradeoffs between latency, freshness, and cost. This is data engineering where performance and efficiency directly impact customer experience and unit economics.

Company Details: Supply Chain AI, Startup with Strong Revenue Growth, 40+ Employees
Compensation: Base $170,000-$220,000 (depending on experience and work location)+ bonus + equity
Location: Ability to work hybrid in Mountain View, CA **OR** Boulder, CO.

Who You Are

• Passionate about elegant data architecture and brutal efficiency
• An optimizer who sees cost and performance as design constraints, not afterthoughts
• Builder of systems that are fast, reliable, and maintainable

What You’ll Do

• Design and build data pipelines, models, and APIs that power customer-facing applications
• Optimize data layers for the best tradeoff of performance, freshness, and cost (we process millions of events daily—efficiency matters)
• Partner with Data Scientists and ML Engineers to translate application requirements into robust data architecture
• Ensure data quality, governance, and reliability across streaming and batch workloads
• Drive hands-on implementation from design through production

Must Have

• 3-5 years of data engineering experience building production data systems
• Strong experience with cloud data platforms (GCP/BigQuery strongly preferred)
• Proficiency in SQL, Python, and data orchestration tools (Airflow, DBT)
• Experience building APIs for data-intensive applications (FastAPI or similar)
• Track record of optimizing data systems for cost and performance at scale
• Genuine desire to work in a fast-paced startup environment

Nice to Have

• Big data tools experience (Spark, Presto/Trino, k8s)
• Query optimization and cost management experience
• Experience with streaming/real-time data systems
• Building data systems that integrate with ML/AI models
• Startup experience