Job at a glance
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. 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. We recognize that no one person will embody every single quality or skill listed below. If you are passionate about data engineering, cloud platforms, automation, and delivering meaningful business insights, we encourage you to apply.
Education: Requires a bachelor’s or foreign equivalent degree in computer science, information technology or a technology related field Master’s degree in Computer Science, Data Engineering, Analytics, or a related quantitative field is preferred. Experience: 5+ years of professional experience in data engineering, data-platform engineering, analytics engineering, or a related discipline.
Experience designing, building, deploying, and supporting scalable data pipelines and cloud-based data solutions. Experience working with business stakeholders to translate data requirements into technical solutions and actionable insights. Strong communication, analytical, problem-solving, and stakeholder-management skills. Ability to work independently and collaboratively within a cross-functional, Agile delivery environment.
Required Technical Experience: Strong SQL skills, including the ability to write complex queries, optimize performance, and manage large-scale datasets. Hands-on experience with BigQuery and PostgreSQL database technologies, including pgAdmin or comparable database-management tools. Intermediate to advanced Python coding skills, with experience devel