Human-shared robotics for material movement and task assistance in logistics, healthcare, and manufacturing.
Founded
2022
Industry
Robotics
Funding Track Record
Seed
USD 10,000,000
Reported prior to July 2023.
Series A- 2023-07-26
USD 30,000,000
Round reported July 26, 2023.
Series B- 2024-04-10
Funding event dated April 10, 2024; financial total obfuscated in reporting.
Investor Signal
“Backers include Sequoia Capital, Khosla Ventures, Mayo Clinic, General Catalyst, Lux Capital, Bison Ventures, Industry Ventures and other institutional investors.”
Founders
What we do
Join the Team
Senior Data Infrastructure Engineer
On-SiteSan Francisco Bay Area, US
On-Site • San Francisco Bay Area, US
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Who you are
5+ years of professional experience in data engineering or data infrastructure roles
Strong proficiency in Python and SQL, with the ability to write production-quality, scalable, and well-tested code
Proven experience designing and operating ingestion pipelines and staging layers (streaming and batch) that support downstream analytics and product use cases
Experience deploying and managing cloud data infrastructure in AWS using infrastructure-as-code (e.g., Terraform, Kubernetes, Docker)
Hands-on experience with cloud-based data platforms, storage systems, and infrastructure
Familiarity with data quality practices, testing frameworks, and CI/CD for data pipelines
Highly motivated teammate with excellent oral and written communication skills
Enjoy working in a fast paced, collaborative and dynamic start-up environment as part of a small team
Willingness to travel occasionally for on-site support or testing, as needed
Must have and maintain US work authorization
Proven experience as the technical owner or lead for a data ingestion platform or foundational data system
Experience with Databricks (Delta Live Tables, SQL Warehouse) and familiarity with dbt or similar tools to support analytics engineers
Strong understanding of multi-tenant architectures, with a track record of balancing cost-efficiency, performance, and reliability at scale
Background in streaming systems (Kafka, Flink, Kinesis, or Spark Structured Streaming)
Familiarity with data quality and observability tools (e.g., Great Expectations, Monte Carlo)
Exposure to IoT/robotics telemetry or 3D/spatial data processing (e.g., point clouds, LiDAR, time-series)
Experience working in a product-facing data role, collaborating directly with product, engineering, and AI/ML teams to deliver data systems that enable new customer-facing features
Demonstrated ability to translate product requirements into scalable data solutions with measurable business impact
What the job involves
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This role is ideal for engineers who enjoy working at the intersection of streaming systems, analytics platforms, and mission-critical operations
You’ll collaborate across robotics, AI, and product teams to architect and scale the backbone that powers Vista (our AI insights layer) and ScoutMap (our 3D mapping and environment intelligence system)
From streaming ingestion to analytics-ready marts, your work will ensure our customers can ask “what’s happening now?”—whether it’s the state of a robot fleet, the readiness of a facility, or the flow of critical tasks—and always get fast, reliable answers
Own the full ingestion path from edge to cloud, ensuring robot telemetry, sensor data, and warehouse events are reliably captured, transported, and made available for downstream systems
Design, build, and operate scalable pipelines and foundational data layers (streaming and batch) that deliver low-latency, reliable data for analytics, AI/ML, and product features
Build and maintain ingestion pipelines from object storage (e.g., S3) into Databricks, including raw → staged → analytics-ready layers, supporting both streaming and batch workloads
Own the reliability and CI/CD of the data warehouse and foundational data layers, enabling safe, repeatable deployment of schema changes, transformations, and infrastructure that analytics engineers depend on
Implement observability, monitoring, and data quality checks to ensure pipeline correctness, detect failures or drift, and maintain trust in data used by Vista, Portal, and Scoutmap
Scale and optimize multi-tenant data infrastructure, balancing performance, reliability, and cost-efficiency as Cobot’s customer base and data volume grow
Collaborate directly with robotics, AI/ML, product, and analytics teams to translate product requirements into resilient data systems that unlock customer-facing features
Establish and enforce best practices for data engineering, reliability, security, and CI/CD across ingestion, staging, and warehouse layers—owning the foundations while enabling analytics engineers to ship metrics, marts, and dashboards efficiently
