Senior Data Engineer - Remote, Scale Data Platform

Alpaca

United States

On-site

USD 150,000 - 190,000

Full time

14 days+

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Job summary

Alpaca, a US-headquartered, global leader in brokerage infrastructure, is seeking a Senior Data Engineer to scale its data platform for large customers and new jurisdictions. You will work with open-source data tools on Google Cloud, building streaming and batch ingestion, lakehouse governance, and BI access for internal and external stakeholders.

The role emphasizes distributed systems, low-latency pipelines, and infrastructure as code in a fast-paced startup environment with a 100%

Qualifications

  • 5+ years in Data Engineering with large-scale pipelines.
  • Experience operating scalable data platforms >100M events/day.
  • Hands-on Kubernetes with Docker and Helm.
  • IaC experience: Terraform, Ansible, ArgoCD.
  • Experience with Google Cloud Platform data services.
  • Python and SQL for building pipelines.

Responsibilities

  • Design, build, and evolve the core data platform infrastructure.
  • Own lakehouse infrastructure as code, deployments via Terraform/Ansible on Kubernetes.
  • Build and scale low-latency streaming and batch ingestion pipelines.
  • Develop and scale BI access to lakehouse data for downstream teams.
  • Enforce reliability, monitoring, on-call rotations, and SLAs.
  • Collaborate with DevOps and Analytics Eng to close gaps.

Skills

Distributed systems
Kubernetes
Python
SQL
Data pipeline design
Cloud tooling

Tools

Apache Iceberg
Kafka
Debezium
Airflow
Terraform
Ansible
ArgoCD
GKE/Kubernetes

Job description

Alpaca, a US-headquartered, global leader in brokerage infrastructure, is seeking a Senior Data Engineer to scale its data platform for large customers and new jurisdictions. You will work with open-source data tools on Google Cloud, building streaming and batch ingestion, lakehouse governance, and BI access for internal and external stakeholders.

The role emphasizes distributed systems, low-latency pipelines, and infrastructure as code in a fast-paced startup environment with a 100%

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