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Data Platform Engineer

1 month, 1 week ago
United States
Full-time
Mid Level
Data Engineer
Software Development
Ansible Apache Airflow Apache Spark Docker Encryption Go gRPC Helm InfluxDB Kafka Kubernetes Machine Learning PostgreSQL Python REST API Terraform TimescaleDB
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Apptronik

Apptronik

Apptronik develops versatile humanoid robots to tackle tasks humans prefer not to do, aiming to reshape existence and enhance universal quality of life.

Aerospace & Defense
51-250
Founded 2015
$23M raised
View All Jobs 69

Description

  • Design and maintain backend data services and pipelines for telemetry, sensor, and training data ingestion, processing, and serving.
  • Build batch and streaming data workflows that integrate on-robot data sources, cloud infrastructure, and enterprise systems.
  • Develop internal APIs and platform tooling that enable machine learning, robotics, and software teams to access trusted data securely and efficiently.
  • Establish data quality, lineage, and governance practices to improve confidence in datasets used for training, analytics, and operational decisions.
  • Monitor and optimize storage systems, database performance, and resource utilization to meet scalability, throughput, and latency needs.
  • Collaborate with data scientists, machine learning engineers, robotics engineers, SRE, and security teams to deliver production-ready infrastructure.
  • Support secure deployment patterns including encryption, access controls, and reliable operation across cloud and hybrid environments.
  • Stay current on data engineering practices, distributed systems design, and emerging technologies relevant to robotics and machine learning platforms.

Requirements

  • Strong proficiency in Python; Go experience for backend service implementation is preferred.
  • Experience with real-time and batch pipeline frameworks such as Kafka, Spark, Airflow, or comparable technologies.
  • Strong command of relational databases such as PostgreSQL and familiarity with NoSQL stores; experience with time-series data is a plus.
  • Proficiency with cloud platforms and hands-on experience with infrastructure tooling such as Terraform, Helm, or Ansible.
  • Experience with Kubernetes and Docker for deploying and scaling backend and data services.
  • Familiarity with encryption, RBAC, and secure service-to-service or user-to-service data access patterns.
  • Experience building observability dashboards and alerting for data pipelines and platform services.
  • Experience building REST APIs or gRPC services for data access, integration, and internal platform use.
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.
  • Minimum of 3 years of professional, full-time experience in data engineering, backend engineering, or a closely related discipline.
  • Experience building data pipelines or platform infrastructure used to support machine learning, analytics, or AI workflows.
  • Preferred: Experience in robotics, autonomous systems, data platforms, or machine learning infrastructure.
  • Preferred: Familiarity with time-series data stores such as InfluxDB or TimescaleDB for telemetry-heavy workloads.
  • Preferred: Experience with data catalog, lineage, or governance tooling.
  • Preferred: Knowledge of streaming architectures and event-driven systems in production environments.

Interested in this position?

Apply directly on the company website

Apply Now

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