Join Contoro Robotics – Revolutionizing Warehouse Automation with Cutting-Edge Robotics
At Contoro Robotics, we're on a mission to solve labor challenges through advanced robotic solutions. Headquartered in Austin, TX, our fast-growing startup is transforming the supply chain industry with our flagship warehouse automation technology. Our team is made up of top-tier experts in robotics, AI, and logistics, working together to push the boundaries of automation.
We’re looking for talented and ambitious individuals to join us on this journey—helping shape the future of robotics while growing alongside a world-class team. If you're passionate about innovation, problem-solving, and making a real-world impact, we want to hear from you!
Job Description
Title: Data Engineer
Intro
Contoro Robotics is an Austin-based startup revolutionizing warehouse automation with AI-powered robotic solutions tackling real industrial challenges. Our mission is to deploy scalable, human-in-the-loop autonomous systems that reliably perform in the field.
We're looking for a talented Software Engineer to help scale our Cloud Platform Analytics Data Pipeline. This pipeline enables critical decision making across multiple teams at Contoro. You’ll own the key components of metrics instrumentation, validation and aggregation - with the ultimate goal of empowering internal teams with the data they need to be more effective.
Job Responsibilities
End-to-End Analytics Data Pipeline
Own the company-wide catalog of metrics, events, schemas, and data contracts
Ensure telemetry is correctly instrumented across products and edge cases
Design and evolve event-driven data architectures, including telemetry ingestion, schema evolution, and downstream data consumers
Improve the reliability, scalability, and observability of data pipelines spanning robots and cloud systems
Analytics Data Quality
Develop automated tests and validation systems to ensure telemetry accuracy and prevent regressions
Monitor and improve data quality, schema compliance, and end-to-end metric delivery
Establish best practices for analytics instrumentation, testing, and governance
Analytics Reporting
Design and maintain analytical data models, aggregations, and pre-calculated metrics for fast reporting
Develop performant SQL queries and time-series analytics pipelines
Build self-service analytics capabilities, metrics APIs, and reporting datasets that enable teams to reliably consume operational data at scale
Qualification Requirements
Please apply only if you have professional experience building production data pipelines, analytics platforms, telemetry systems, or event-driven architectures.
Experience
3+ years of experience building and maintaining production data pipelines
Experience designing event schemas, data contracts, or analytics data models
A proven track record of supporting business analytics, reporting, or operational metrics
Technical Expertise
Proficiency with Python, Docker, and SQL databases in a production software environment
Strong SQL skills, including aggregations, time-series analysis, and query optimization
Experience with data pipeline technologies (e.g., Kafka, MQTT, Fluent Bit, PostgreSQL, TimescaleDB)
Experience building automated tests to ensure data accuracy and pipeline reliability
Soft Skills
Strong sense of ownership, urgency, and curiosity
Excellent communication skills—both verbal and written
Ability to work collaboratively across cross-functional teams
Education
Minimum B.S. in Computer Science, Engineering, or related field (or equivalent industry experience)
Work Location
Willingness to work on-site at our Austin, TX headquarters
Preferred Experience
Experience with data ingestion, workflow orchestration, and stream processing technologies (e.g., Fluent Bit, Kafka Connect, Airflow, Dagster, Prefect)
Familiarity with schema management and data contracts (JSON Schema, Avro, Protobuf, etc.)
Experience with robotics, IoT, industrial automation, or other distributed edge-connected systems
Knowledge of analytics platforms and visualization tools such as Grafana
Familiarity with AWS services and cloud-native architectures
