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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Full Stack Data Engineer - **Company:** Ford Motor Company - **Location:** Dearborn, MI, United States - **Experience:** Experienced - **Salary:** $85,400.0 - $143,200.0 - **Contract:** Permanent contract - **Skills:** Clean Code Principles, Agile Methodology, Data Analysis, Automation of Tests, Big Data, BigQuery, Cloud Engineering, Cloud Storage, Software Quality, Code Review, Continuous Delivery, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Mapping, Data Systems, Data Warehousing, DevOps, Distributed Data Store, Data Flow Control, Python (Programming Language), Operational Databases, Cloud Services, Software Deployment, Software Engineering, SonarQube, SQL Databases, Data Streaming, User-Centered Design, Google Cloud, Test-Driven Development (TDD), Data Ingestion, Spring Cloud, Apache Spark, Software Troubleshooting, Containerization, Infrastructure Automation Frameworks, Information Technology, Data Lineage, Production Code, Data Analytics, Checkmarx, Api Design, Terraform, Software Version Control, Data Pipelines, Docker, Vulnerability Analysis, Programming Languages - **Published:** August 5, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=eef1687719f12bcd ## About the Role * Bachelor's degree or foreign equivalent in Computer Science, Information Technology, or a technology-related field., * 3+ 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 Experience * Strong 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 Experience * Experience 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. ## Description 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. * Pipeline 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 data 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. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Remote Driving on Plant Grounds with State-of-the-Art Cloud Technologies](https://www.wearedevelopers.com/videos/251-remote-driving-on-plant-grounds-with-state-of-the-art-cloud-technologies) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [Got AI ideas but no money? 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