Remote Senior Data Platform Engineer

Orca AI

United States

Remote

USD 100.000 - 145.000

Vollzeit

Vor 6 Tagen
Sei unter den ersten Bewerbenden

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Zusammenfassung

Orca AI is seeking a Senior Data Platform Engineer for a fully remote role limited to Athens metropolitan area. You will design, build, and evolve our data infrastructure powering analytics, AI workloads, and large-scale model execution.

You will own end-to-end data ingestion, data lake architecture, and scalable pipelines, while guiding the team on best practices around infrastructure, CI/CD, and performance optimization.

Qualifikationen

  • 5+ years of experience as a Data Platform/Infra Engineer.
  • Experience building scalable data infrastructure in Data Lake architectures.
  • Experience operating large-scale data workloads on Kubernetes with KEDA autoscaling.
  • Strong Python and SQL skills; IaC with Terraform.
  • Experience with data orchestration platforms such as Airflow or Prefect, and Snowflake.

Aufgaben

  • Build high-volume batch and near-real-time ingestion services and scale streaming capabilities.
  • Design and implement data solutions in a distributed microservices environment.
  • Develop and optimize large-scale data pipelines for batch and streaming use cases.
  • Ensure data quality, governance, and compliance.
  • Manage Kubernetes infrastructure with dynamic scaling (KEDA) and Terraform provisioning.
  • Provide technical guidance and promote best practices for infrastructure, CI/CD, and system design.
  • Investigate memory management and performance tuning for cost-effective, fast-distributed systems.

Kenntnisse

Python
SQL
Kubernetes
Data Lake architectures
Data pipelines
Infrastructure as Code
Terraform
KEDA
Airflow
Prefect
Snowflake

Tools

Terraform
Airflow
Prefect
KEDA
Snowflake
Kubernetes

Jobbeschreibung

Orca AI is seeking a Senior Data Platform Engineer for a fully remote role limited to Athens metropolitan area. You will design, build, and evolve our data infrastructure powering analytics, AI workloads, and large-scale model execution.

You will own end-to-end data ingestion, data lake architecture, and scalable pipelines, while guiding the team on best practices around infrastructure, CI/CD, and performance optimization.

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