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Job Overview
Location
Zurich
Job Type
Full-time
Category
Data Engineer
Date Posted
September 15, 2025
Full Job Description
đź“‹ Description
- • Own the end-to-end design and implementation of a scalable data pipeline that ingests, cleans, and stores terabytes of high-frequency sensor, actuator, and telemetry data generated by our fleet of autonomous excavators and simulation environments.
- • Architect and maintain cloud-native data infrastructure (AWS S3, Redshift, Glue, Lambda, Step Functions) that guarantees sub-minute latency for operational dashboards and supports long-term trend analytics for strategic decision-making.
- • Build robust ETL/ELT workflows that transform raw machine logs, LiDAR point clouds, GNSS tracks, and CAN-bus signals into curated, query-ready datasets that power both engineering debug sessions and executive KPI reports.
- • Develop intuitive data models and schema designs that balance query performance with storage cost; continuously profile and optimize queries to cut dashboard load times by 50 % and reduce monthly cloud spend.
- • Create automated data-quality monitors and anomaly-detection alerts that flag missing packets, sensor drift, or unexpected machine behavior within minutes—enabling field engineers to react before costly downtime occurs.
- • Collaborate daily with perception, controls, and simulation teams to translate research-grade prototypes into production-grade analytics features; your code will directly influence how operators interact with machines in our gamified control center.
- • Design self-service BI tools (Metabase, Superset) that let non-technical stakeholders slice and dice data without writing SQL; empower finance, operations, and customer-success teams to answer their own questions in real time.
- • Build lightweight Python/C++ micro-services that expose REST and gRPC endpoints for on-demand data retrieval, enabling downstream ML training pipelines to pull fresh datasets with zero manual intervention.
- • Establish rigorous version control, CI/CD, and automated testing for every data artifact—treat data as a product, ensuring reproducibility and rollback capabilities across releases.
- • Document architecture decisions, data dictionaries, and runbooks in Notion and Confluence so that new team members can ramp up within days, not weeks.
- • Present weekly findings to the executive team: translate complex statistical insights into clear narratives that influence roadmap priorities, customer pricing, and go-to-market strategy.
- • Champion a culture of data-driven experimentation by running A/B tests on operator UI changes and quantifying the impact on productivity, safety, and fuel efficiency.
- • Contribute to open-source communities and publish technical blog posts about novel techniques in construction-tech data engineering—position Gravis as a thought leader in heavy-machine autonomy analytics.
🎯 Requirements
- • Bachelor’s degree (or higher) in Computer Science, Data Engineering, Robotics, or a related quantitative field
- • Demonstrated experience designing and operating production-grade data pipelines using Python or C++ in cloud environments (AWS preferred)
- • Solid SQL skills and familiarity with relational and columnar databases; hands-on experience with data warehousing concepts
- • Clear written and verbal communication in English; ability to explain technical trade-offs to both engineers and business stakeholders
- • Nice-to-have: prior exposure to time-series data, robotics telemetry, or construction-equipment domains; familiarity with infrastructure-as-code tools like Terraform or Pulumi
🏖️ Benefits
- • Six-month paid internship located in vibrant Zurich with a fair market salary and the possibility of extension or conversion to a full-time role
- • Hybrid work model and flexible hours—tailor your schedule around deep-focus coding blocks or field visits to live construction sites
- • Direct mentorship from founders and senior engineers who have over a decade of experience in large-scale robotics and machine learning
- • Access to cutting-edge sensor suites, high-performance GPU clusters, and a rooftop testbed where you can see your data pipelines drive real 20-ton excavators autonomously
- • International, inclusive team culture with regular team retreats, hackathons, and a generous learning budget for courses, conferences, and certifications
Skills & Technologies
Python
AWS
Junior
Remote
Degree Required
About Gravis Robotics AG
Gravis Robotics AG develops AI-driven software that transforms heavy construction machines into autonomous robots. The Zurich-based spin-off of ETH Zurich combines machine learning, perception, and motion-planning to let excavators, dozers, and compactors work without human operators, increasing productivity and safety on job sites while reducing fuel consumption and emissions.
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