Full Stack Data Engineer

Ford Motor CompanyDearborn, MI
$99,600 - $192,900

About The Position

As a Data Engineer, you will design and scale robust batch and streaming data pipelines on the Google Cloud Platform (GCP). You will build exceptional analytical data products rooted in solid data warehousing principles. Working in an agile, customer-centric environment, you will champion modern software engineering practices. You will manage and scale our platform’s infrastructure using Terraform (Infrastructure as Code) and continuously deliver high-quality code through robust CI/CD pipelines. As collaboration is key, you will partner closely with analytics stakeholders to streamline how data is acquired, processed, and presented. Security and quality are built into everything we do. You will proactively monitor data quality, document data lineage, and address code vulnerabilities using modern DevSecOps tools. Additionally, you will optimize our existing data solutions to ensure they are highly secure, reliable, cost-effective, and performing at their peak, while providing critical production support to keep our pipelines running smoothly.

Requirements

  • Experience designing and scaling batch and streaming data pipelines on GCP.
  • Proficiency in data warehousing principles.
  • Experience with modern software engineering practices.
  • Experience managing and scaling infrastructure using Terraform (Infrastructure as Code).
  • Experience with robust CI/CD pipelines.
  • Experience monitoring data quality and documenting data lineage.
  • Experience addressing code vulnerabilities using DevSecOps tools.
  • Experience optimizing data solutions for security, reliability, cost-effectiveness, and performance.
  • Experience providing production support for data pipelines.

Responsibilities

  • Design and scale robust batch and streaming data pipelines on the Google Cloud Platform (GCP).
  • Build exceptional analytical data products rooted in solid data warehousing principles.
  • Champion modern software engineering practices in an agile, customer-centric environment.
  • Manage and scale platform infrastructure using Terraform (Infrastructure as Code).
  • Continuously deliver high-quality code through robust CI/CD pipelines.
  • Partner closely with analytics stakeholders to streamline data acquisition, processing, and presentation.
  • Proactively monitor data quality and document data lineage.
  • Address code vulnerabilities using modern DevSecOps tools.
  • Optimize existing data solutions for security, reliability, cost-effectiveness, and peak performance.
  • Provide critical production support to ensure smooth pipeline operation.
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