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2 дня назад

Cloud Platform - Data Engineer (Robotics)

130 000 - 164 500$
Формат работы
onsite
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
US
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR
Cloud Platform - Data Engineer (Robotics): Building ETL pipelines, data warehouses, dashboards, and ML training infrastructure for a robotics fleet with an accent on robot telemetry, BigQuery, Kubernetes, and reproducible computer vision workflows. Focus on designing reliable data platforms, optimizing warehouse queries, productionizing model training, and ensuring observability for data pipelines running in the field.

Location: Pittsburgh, PA, United States; onsite five days a week

Salary: $130,000–$164,500 per year, plus potential equity awards and an annual performance-based bonus.

Company

hirify.global Robotics develops and deploys robots for direct-to-customer food production and online food delivery.

What you will do

  • Build and maintain ETL pipelines that ingest, validate, transform, and load robot telemetry into BigQuery.
  • Manage ML training workflows with Argo Workflows on Kubernetes, from data extraction through model evaluation and registration.
  • Design data quality checks, observability dashboards, and infrastructure for Superset and Grafana.
  • Own warehouse schemas, incremental loading, dbt transformations, and BigQuery/Athena query optimization.
  • Collaborate with data scientists to productionize reproducible model-training workflows.
  • Contribute to Terraform infrastructure-as-code, CI/CD pipelines, and on-call reliability rotations.

Requirements

  • 2+ years of experience in data engineering, ML infrastructure, or analytics engineering.
  • Strong experience with workflow orchestration tools such as Argo Workflows, Airflow, or Prefect.
  • Production-quality Python data pipelines using pandas, SQL, and dbt.
  • Experience with cloud data services such as BigQuery, Athena, S3, or GCP equivalents.
  • Experience building or maintaining ML training pipelines, plus Docker and Kubernetes basics.
  • Fluency in SQL, query performance optimization, documentation, and design documents.

Nice to have

  • ETL debugging, data quality frameworks, and anomaly detection experience.
  • Hybrid AWS and GCP cloud experience.
  • Robotics, IoT, or real-world sensor data experience.
  • Additional experience with dbt transformations and warehouse modeling.

Culture & Benefits

  • Collaborative environment with support and guidance from experienced colleagues and managers.
  • Medical, dental, and vision insurance, including HSA options.
  • Company-paid life and disability insurance, plus optional supplemental insurance plans.
  • 401(k), healthcare, dependent care, and commuter flexible spending accounts.
  • Discretionary vacation, paid holidays, sick time, bereavement leave, and parental leave.

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