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Ford is hiring a Global Data Insight & Analytics engineer to design and maintain scalable data pipelines on GCP. You will implement governance, security, and cost-optimized data flows, collaborating with architects and cross-functional teams.
The role emphasizes end-to-end data solutions, automation, and continuous learning, with a hybrid work model and strong salary range for a Grade 8 position. VISA sponsorship available for eligible candidates.
We made history and now we work to transform the future – for our customers, our communities and our families. You'll see your work on the road every day, helping people move freely and pursue their dreams. At Ford, you can build more than vehicles. Come build what matters.
Do you believe data tells the real story? We do! Redefining mobility requires quality data, metrics and analytics, as well as insightful interpreters and analysts. That's where Global Data Insight & Analytics makes an impact. We advise leadership on business conditions, customer needs and the competitive landscape. With our support, key decision makers can act in meaningful, positive ways. Join us and use your data expertise and analytical skills to drive evidence-based, timely decision making.
We're seeking a highly skilled and experienced Full Stack Data Engineer to play a pivotal role in the development and maintenance of our Enterprise Data Platform. In this role, you'll be responsible for designing, building, and optimizing scalable data pipelines within our Google Cloud Platform (GCP) environment. You'll work with GCP Native technologies like BigQuery, Dataflow, and Pub/Sub, ensuring data governance, security, and optimal performance. This is a fantastic opportunity to leverage your full-stack expertise, collaborate with talented teams, and establish best practices for data engineering at Ford.
Data Pipeline Architect & Builder:Spearhead the design, development, and maintenance of scalable data ingestion and curation pipelines from diverse sources. Ensure data is standardized, high-quality, and optimized for analytical use. Leverage cutting-edge tools and technologies, including Python, SQL, and DBT/Dataform, to build robust and efficient data pipelines.
End-to-End Integration Expert:Utilize your full-stack skills to contribute to seamless end-to-end development, ensuring smooth and reliable data flow from source to insight.
GCP Data Solutions Leader: Leverage your deep expertise in GCP services (BigQuery, Dataflow, Pub/Sub, Cloud Functions, etc.) to build and manage data platforms that not only meet but exceed business needs and expectations.
Data Governance & Security Champion: Implement and manage robust data governance policies, access controls, and security best practices, fully utilizing GCP's native security features to protect sensitive data.
Data Workflow Orchestrator: Employ Astronomer and Terraform for efficient data workflow management and cloud infrastructure provisioning, championing best practices in Infrastructure as Code (IaC).
Performance Optimization Driver: Continuously monitor and improve the performance, scalability, and efficiency of data pipelines and storage solutions, ensuring optimal resource utilization and cost-effectiveness.
Collaborative Innovator: Collaborate effectively with data architects, application architects, service owners, and cross-functional teams to define and promote best practices, design patterns, and frameworks for cloud data engineering.
Automation & Reliability Advocate: Proactively automate data platform processes to enhance reliability, improve data quality, minimize manual intervention, and drive operational efficiency.
Effective Communicator: Clearly and transparently communicate complex technical decisions to both technical and non-technical stakeholders, fostering understanding and alignment.
Continuous Learner: Stay ahead of the curve by continuously learning about industry trends and emerging technologies, proactively identifying opportunities to improve our data platform and enhance our capabilities.
Business Impact Translator: Translate complex business requirements into optimized data asset designs and efficient code, ensuring that our data solutions directly contribute to business goals.
Documentation & Knowledge Sharer: Develop comprehensive documentation for data engineering processes, promoting knowledge sharing, facilitating collaboration, and ensuring long-term system maintainability.
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:
This position is a salary grade 8 and ranges from $115,000-$192,900.
Final determination of salary grade will be based on candidate's skills and experience, and base salary will be set within the applicable range according to job scope, responsibility and competitive market value.
Internal applicants: moving into this role may result in an adjustment to your current compensation based on the posted pay range for this role, taking into consideration your qualifications and other relevant factors.
Visa sponsorship is available for this position.
Domestic relocation is not available for this position.
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. 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 1-888-336-0660.
This position is hybrid with a requirement to be onsite four or more days per week.