Data Engineer, Cloud Platform

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