Data Engineer, Cloud Platform

Join Contoro Robotics – Revolutionizing Warehouse Automation with Cutting-Edge RoboticsAt 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 DescriptionTitle: Data EngineerIntroContoro 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 ResponsibilitiesEnd-to-End Analytics Data PipelineOwn the company-wide catalog of metrics, events, schemas, and data contractsEnsure telemetry is correctly instrumented across products and edge casesDesign and evolve event-driven data architectures, including telemetry ingestion, schema evolution, and downstream data consumersImprove the reliability, scalability, and observability of data pipelines spanning robots and cloud systemsAnalytics Data QualityDevelop automated tests and validation systems to ensure telemetry accuracy and prevent regressionsMonitor and improve data quality, schema compliance, and end-to-end metric deliveryEstablish best practices for analytics instrumentation, testing, and governanceAnalytics ReportingDesign and maintain analytical data models, aggregations, and pre-calculated metrics for fast reportingDevelop performant SQL queries and time-series analytics pipelinesBuild self-service analytics capabilities, metrics APIs, and reporting datasets that enable teams to reliably consume operational data at scaleQualification RequirementsPlease apply only if you have professional experience building production data pipelines, analytics platforms, telemetry systems, or event-driven architectures.Experience3+ years of experience building and maintaining production data pipelinesExperience designing event schemas, data contracts, or analytics data modelsA proven track record of supporting business analytics, reporting, or operational metricsTechnical ExpertiseProficiency with Python, Docker, and SQL databases in a production software environmentStrong SQL skills, including aggregations, time-series analysis, and query optimizationExperience with data pipeline technologies (e.g., Kafka, MQTT, Fluent Bit, PostgreSQL, TimescaleDB)Experience building automated tests to ensure data accuracy and pipeline reliabilitySoft SkillsStrong sense of ownership, urgency, and curiosityExcellent communication skills—both verbal and writtenAbility to work collaboratively across cross-functional teamsEducationMinimum B.S. in Computer Science, Engineering, or related field (or equivalent industry experience)Work LocationWillingness to work on-site at our Austin, TX headquartersPreferred ExperienceExperience 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 systemsKnowledge of analytics platforms and visualization tools such as GrafanaFamiliarity with AWS services and cloud-native architectures