Data Engineer - Mobile Mapping & AI Infrastructure (m/f/d)

Data Engineer – Mobile Mapping & AI Infrastructure (m/f/d)

The Role

As a Data Engineer you'll join one of our clients through Meyer Talent Acquisition. You are the architect of the "data refinery." The 360-degree cameras and LiDAR sensors generate petabytes of raw street-level data every year. Your mission is to build the robust, cloud-native infrastructure that ingests, processes, and prepares this massive geospatial volume for our Computer Vision (CV) and Machine Learning models. You will bridge the gap between raw sensor acquisition and production-ready AI, ensuring that our "Digital Twin" of the world is updated with pinpoint accuracy and maximum efficiency.

Key Responsibilities

• Orchestration & Pipelines: Design and manage complex, multi-stage data workflows using Flyte to automate the transition from raw sensor data to ML- ready datasets.
• Scalable Infrastructure: Maintain and scale processing clusters on Azure Kubernetes Service (AKS), ensuring high availability and cost-efficient resource allocation for GPU/CPU-heavy tasks.
• CV Data Engineering: Build specialized pipelines for Computer Vision, including automated data versioning, quality gates, and Active Learning loops.
• Geospatial Data Lifecycle: Manage large-scale storage and retrieval patterns for LiDAR and imagery, optimizing data formats for low-latency access by both humans and algorithms.
• MLOps Collaboration: Work alongside ML Researchers to industrialize research code, turning experimental Python scripts into hardened, reproducible production workflows. Technical Requirements
• Data Orchestration: Extensive experience with Flyte (or Airflow/Prefect), building resilient, versioned, and reproducible pipelines.
• Cloud & Containers: Deep proficiency in Azure and Kubernetes - Helm charts, K8s operators, cloud-native storage.
• Python Mastery: Expert-level Python, particularly for high-performance data manipulation (Pandas, NumPy) and interfacing with CV libraries.
• Data Architecture: Strong understanding of modern data stack patterns (Lakehouse/Mesh) and experience handling unstructured data (images, point clouds, video).
• DevOps Mindset: Infrastructure as Code (Terraform) and CI/CD pipelines experience.

What We Offer

• Massive Scale: Work with one of the largest specialised geospatial datasets in the world (180+ million panoramic images yearly).
• Cutting-Edge Stack: A "no-legacy" approach to MLOps - utilising the best modern tools to solve problems others haven't encountered yet.
• Flexible working: Async-first culture. Vienna office anchor day Wednesday.
• English working language - German not required.