Data Engineer

The Pro360 team is tasked with creating a seamless, data-driven ecosystem for Ford Pro. In this role, you will be responsible for the end-to-end data lifecycle-from ingestion and transformation to visualization and executive presentation.

You will work within a modern tech stack centered on the Google Cloud Platform, utilizing your expertise in SQL and Python to build scalable pipelines. Uniquely, this role bridges the gap between traditional data engineering and DevOps, as you will manage infrastructure using Terraform and Tekton. Beyond the technical build, you will act as a consultant to the business, using Looker Studio and the Microsoft Office suite to present insights that influence strategic decisions at management level.

As a Data Engineer within the Pro360 division of Ford's Global Data Insight & Analytics (GDI&A) organization, you will play a pivotal role in architecting the data foundations that drive our commercial business forward. This role is designed for a technical expert who excels at building robust data pipelines, managing cloud infrastructure as code, and translating complex datasets into compelling visual narratives for stakeholders and leadership.

• Design, develop, maintain, and optimize complex data pipelines using Astronomer, Apache Airflow, and related orchestration technologies.
• Build scalable data ingestion, transformation, validation, and processing solutions across structured and semi-structured data sources.
• Deploy and manage cloud-based data services on Google Cloud Platform, including BigQuery, Dataflow, and Cloud Run.
• Write advanced SQL queries to extract, transform, analyze, and optimize large-scale datasets.
• Develop clean, maintainable Python code for data transformation, automation, workflow development, and analysis.
• Design and support data models, datasets, and reporting layers that enable trusted business intelligence and analytics.
• Use Terraform to provision and manage cloud infrastructure through Infrastructure as Code practices.
• Build and maintain CI/CD automation using Tekton, GitHub, and related DevOps tools.
• Implement data-quality controls, monitoring, error handling, and operational-support practices to ensure pipeline reliability and data accuracy.
• Build intuitive dashboards and reporting solutions in Looker Studio to track key performance indicators and provide visibility to business stakeholders.
• Partner with business teams and leadership to understand data needs, define reporting requirements, and align data strategy with business goals.
• Translate technical findings and complex data insights into clear, concise, and actionable presentations for non-technical audiences.
• Use Microsoft Office tools, including PowerPoint and Excel, to develop executive-ready analyses, reports, and presentations.
• Participate in technical design sessions, Agile planning, peer reviews, and continuous-improvement activities.
• Contribute to data-engineering standards, documentation, reusable development patterns, and a collaborative engineering culture.
• Design, develop, maintain, and optimize complex data pipelines using Astronomer, Apache Airflow, and related orchestration technologies.
• Build scalable data ingestion, transformation, validation, and processing solutions across structured and semi-structured data sources.
• Deploy and manage cloud-based data services on Google Cloud Platform, including BigQuery, Dataflow, and Cloud Run.
• Write advanced SQL queries to extract, transform, analyze, and optimize large-scale datasets.
• Develop clean, maintainable Python code for data transformation, automation, workflow development, and analysis.
• Design and support data models, datasets, and reporting layers that enable trusted business intelligence and analytics.
• Use Terraform to provision and manage cloud infrastructure through Infrastructure as Code practices.
• Build and maintain CI/CD automation using Tekton, GitHub, and related DevOps tools.
• Implement data-quality controls, monitoring, error handling, and operational-support practices to ensure pipeline reliability and data accuracy.
• Build intuitive dashboards and reporting solutions in Looker Studio to track key performance indicators and provide visibility to business stakeholders.
• Partner with business teams and leadership to understand data needs, define reporting requirements, and align data strategy with business goals.
• Translate technical findings and complex data insights into clear, concise, and actionable presentations for non-technical audiences.
• Use Microsoft Office tools, including PowerPoint and Excel, to develop executive-ready analyses, reports, and presentations.
• Participate in technical design sessions, Agile planning, peer reviews, and continuous-improvement activities.
• Contribute to data-engineering standards, documentation, reusable development patterns, and a collaborative engineering culture.