Full Stack Data Engineer
$85.4k - $143.2kFord
We are the movers of the world and the makers of the future. We get up every day, roll up our sleeves, and build a better world – together. At Ford, we're all a part of something bigger than ourselves. Are you ready to change the way the world moves?Do you believe data is the engine driving the future of mobility? We do! Transforming how Ford manages, analyzes, and leverages financial data requires scalable data platforms, reliable cloud infrastructure, and high-quality analytical products that enable timely, data-driven decision-making. That’s where the Finance Data Hub makes an impact. We are modernizing how Ford manages financial data globally, delivering trusted and secure data products that support critical finance initiatives across the enterprise.We are seeking a talented and driven Full Stack Data Engineer to join our product team. In this role, you will build scalable, high-performance data pipelines and cloud infrastructure that power financial reporting, analytics, and strategic decision-making. You should have a strong technical background and demonstrate experience in Google Cloud Platform (GCP), data warehousing, batch and streaming pipeline development, infrastructure automation, and modern software engineering practices.Responsibilities include the end-to-end design, development, deployment, optimization, and production support of finance data products—from ingestion and transformation through governance, quality monitoring, and delivery. Working in an Agile, customer-centric environment and in close partnership with analytics stakeholders, product managers, and cross-functional engineers, you will deliver secure, reliable, cost-effective, and high-performing data solutions at enterprise scale.We recognize that no one person will embody every single quality or skill listed below. If you are passionate about data engineering and have a strong foundation in cloud platforms, data architecture, and modern software engineering, we encourage you to apply.EducationBachelor’s degree or foreign equivalent in Computer Science, Information Technology, or a technology-related field.Experience3+ years of strong hands-on experience building and deploying data solutions on Google Cloud Platform.Proven experience designing, developing, and maintaining batch and streaming data ingestion pipelines at scale.2+ years of experience with continuous integration and continuous deployment methodologies and enhancing DevOps capabilities.Experience working in Agile/Scrum environments and collaborating with cross-functional teams.Demonstrated problem-solving skills, analytical thinking, and the ability to communicate complex technical concepts effectively.Ability to work independently while contributing effectively as part of a product-oriented engineering team.Required Technical ExperienceStrong hands-on experience with Google Cloud Platform services used for data engineering and analytics.Experience building scalable batch and streaming data pipelines.Proficiency with Terraform and Infrastructure as Code practices.Strong understanding of data warehousing principles, data modeling, data mapping, and analytical data product design.Experience with data lineage, data quality monitoring, and enterprise data governance standards.Experience with CI/CD pipelines, version control, automated testing, code reviews, and modern DevOps practices.Experience utilizing Test-Driven Development and writing clean, reliable, maintainable code.Familiarity with code quality and vulnerability scanning tools such as SonarQube, Checkmarx, Fossa, and/or Cycode.Strong communication and collaboration skills, including the ability to partner with business stakeholders and advocate for well-designed technical solutions.Customer-centric mindset with strong troubleshooting, optimization, and production-support capabilities.Preferred ExperienceExperience with GCP data services such as BigQuery, Dataflow, Cloud Storage, Pub/Sub, and related cloud-native data technologies.Experience building and deploying cloud-native applications using Python, SQL, or similar programming languages.Experience processing large datasets using Spark or other distributed data-processing frameworks.Experience with containerization technologies such as Docker.Familiarity with Tekton or similar tools for cloud-native automation.Experience developing APIs or service-layer capabilities that enable secure access to data products.Experience in finance, accounting, enterprise financial systems, or financial data domains.Experience supporting production data platforms with defined service-level agreements.You may not check every box, or your experience may look a little different from what we've outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!As an established global company, we offer the benefit of choice. You can choose what your Ford future will look like: will your story span the globe, or keep you close to home? Will your career be a deep dive into what you love, or a series of new teams and new skills? Will you be a leader, a changemaker, a technical expert, a culture builder…or all of the above? No matter what you choose, we offer a work life that works for you, including:Immediate medical, dental, and prescription drug coverageFlexible family care, parental leave, new parent ramp-up programs, subsidized back-up child care and moreVehicle discount program for employees and family members, and management leasesTuition assistanceEstablished and active employee resource groupsPaid time off for individual and team community serviceA generous schedule of paid holidays, including the week between Christmas and New Year’s DayPaid time off and the option to purchase additional vacation time.For a detailed look at our benefits, click here: Benefit Summary This position is a salary grade 6. This position is a salary grade 6 and ranges from $85,400-$143,200.*Visa Sponsorship is not provided for this role*Candidates for positions with Ford Motor Company must be legally authorized to work in the United States. Verification of employment eligibility will be required at the time of hire.We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status. In the United States, If you need a reasonable accommodation for the online application process due to a disability, please call View phone number on click.appcast.io.#LI-Hybrid#LI-GH2Pipeline Development & Ingestion: Design, build, and scale robust batch and streaming data pipelines on Google Cloud Platform (GCP) to process large volumes of finance data.Data Warehousing & Architecture: Develop exceptional analytical data products applying solid data warehouse principles, data modeling, and best practices.Infrastructure & DevOps: Maintain and enhance the platform's infrastructure using Terraform (Infrastructure as Code) and continuously develop, evaluate, and deploy code using CI/CD pipelines.Stakeholder Collaboration: Partner closely with data analytics stakeholders to streamline and optimize data acquisition, processing, and presentation workflows.Data Governance & Quality: Implement and promote enterprise data governance models focusing on data protection, sharing, reuse, standards, quality monitoring, and data lineage documentation.Code Quality & Security: Write clean, reliable code using Test-Driven Development (TDD) in an agile environment, actively addressing security vulnerabilities and code quality issues using tools like SonarQube, Checkmarx, Fossa, and Cycode.Optimization & Cost Management: Continuously optimize existing data solutions (pipelines, infrastructure, and products) to ensure high performance, security, reliability, low vulnerability, and cost efficiency.Production Support: Monitor production pipelines and provide timely production support to resolve issues in accordance with established SLAs.Continuous Improvement: Stay current on modern data engineering practices, contribute to the company's technical direction, and proactively build domain expertise in finance data.Design, build, and scale robust batch and streaming data pipelines on Google Cloud Platform (GCP) to process large volumes of finance dataFull timePosting Date: 2026-08-06
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