Data Platform Engineer

Apptronik Apptronik · Robotics · HQ · Software Engineering

Data Platform Engineer at a robotics company building backend systems for robotic telemetry, sensor, and training data. Focuses on data ingestion, organization, serving, quality, governance, and accessibility for ML, robotics, and analytics teams, supporting both cloud and hybrid environments.

What you'd actually do

  1. Design and maintain backend data services and pipelines for ingesting, processing, and serving telemetry, sensor, and training data generated across development and deployed fleets.
  2. Build robust batch and streaming data workflows that integrate on-robot data sources, cloud infrastructure, and enterprise systems.
  3. Develop internal APIs and platform tooling that enable machine learning, robotics, and software teams to access trusted data efficiently and securely.
  4. Establish data quality, lineage, and governance practices that improve confidence in datasets used for model training, analytics, and operational decision-making.
  5. Monitor and optimize storage systems, database performance, and resource utilization to meet scalability, throughput, and latency requirements.

Skills

Required

  • Python
  • Kafka
  • Spark
  • Airflow
  • PostgreSQL
  • cloud platforms
  • Terraform
  • Helm
  • Ansible
  • Kubernetes
  • Docker
  • encryption
  • RBAC
  • observability dashboards
  • alerting
  • REST APIs
  • gRPC services
  • 3 years of professional experience in data engineering or backend engineering

Nice to have

  • Go
  • NoSQL stores
  • time-series data
  • Machine Learning
  • Robotics
  • AI workflows

What the JD emphasized

  • Experience building data pipelines or platform infrastructure used to support machine learning, analytics, or AI workflows.

Other signals

  • building and maintaining backend systems that ingest, organize, and serve robotic telemetry, sensor, and training data
  • work at the intersection of robotics, cloud infrastructure, and machine learning
  • data is reliable, well-governed, and accessible across both cloud and hybrid deployment environments
  • critical infrastructure for improving Apollo in development and in production