Data Engineer

Ford • Dearborn, MI

10h • Hybrid

About The Position

At Ford Motor Company, we believe freedom of movement drives human progress. We also believe in providing you with the freedom to define and realize your dreams. With our incredible plans for the future of mobility, we have an exciting opportunity for you to join our expanding area of Prognostics.
Are you enthusiastic to mine raw data and realize its hidden value by building amazing, connected data solutions that benefit our customers? Would you love to accelerate our efforts in implementing advanced physics and ML Models in production?
The Data Engineer role resides within the Ford’s Electric Vehicle organization. In this role, you will work on building scalable and robust data pipelines to process large volumes of connected vehicle data to support the Ford vehicle prognostic initiatives.
What you will do...
Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse principles.
Build data pipelines to monitoring quality of data and performance of analytical models.
Maintain the infrastructure of the data platform using terraform and continuously develop, evaluate, and deliver code using CI/CD.
Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process.
Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards.
Enhance and maintain the DevOps capabilities of the data platform.
Continuously optimize and enhance existing data solutions (pipelines, products, infrastructure) for best performance, high security, low vulnerability, low costs, and high reliability.
Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration and continuous deployment (CI/CD).
Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle.
Perform any necessary data mapping, data lineage activities and document information flows.
Monitor the production pipelines and provide production support by addressing production issues as per SLAs.
Provide analysis of connected vehicle data to support new product developments and production vehicle improvements.
Provide visibility to data quality/vehicle/feature issues and work with the business owners to fix the issues.
Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solutions.
Continuously enhance your domain knowledge of connected vehicle data, connected services and algorithms/models developed by data scientists within Ford.
Stay current on the latest data engineering practices and contribute to the technical direction of the company while keeping a customer-centric approach.
You may not check every box, or your experience may look a little different from what we have outlined, but if you think you can bring value to Ford Motor Company, we encourage you to apply!

Requirements

• Master’s degree or foreign equivalent degree in Computer Science, Software Engineering, Information Systems, Data Engineering, or a related field, and 4 years of experience OR equivalent combination of education and experience (6+ years with Bachelor's Degree).
• 4 years of professional experience in: Data engineering, data product development and software product launches
• At least three of the following languages: Java, Python, Spark, Scala, SQL
• 3 years of cloud data/software engineering experience building scalable, reliable, and cost-effective production batch and streaming data pipelines using:
• Data warehouses like Amazon Redshift, Microsoft Azure Synapse Analytics, Google BigQuery.
• Workflow orchestration tools like Airflow.
• Relational Database Management System like MySQL, PostgreSQL, and SQL Server.
• Real-Time data streaming platform like Apache Kafka, GCP Pub/Sub
• Microservices architecture to deliver large-scale real-time data processing application.
• REST APIs for compute, storage, operations, and security.
• DevOps tools such as Tekton, GitHub Actions, Git, GitHub, Terraform, Docker.
• Project management tools like Atlassian JIRA.

Nice To Haves

• Ph.D. or foreign equivalent degree in Computer Science, Software Engineering, Information System, Data Engineering, or a related field.
• 2 years of experience with ML Model Development and/or MLOps.
• Committed code to improve open-source data/software engineering projects
• Experience architecting cloud infrastructure and handling application migrations/upgrades.
• GCP Professional Certifications.
• Demonstrated passion to mine raw data and realize its hidden value.
• Passion to experiment/implement state of the art data engineering methods/techniques.
• Experience working in an implementation team from concept to operations, providing deep technical subject matter expertise for successful deployment.
• Experience implementing methods for automation of all parts of the pipeline to minimize labor in development and production.
• Analytics skills to profile data, troubleshoot data pipeline/product issues.
• Ability to simplify, clearly communicate complex data/software ideas/problems and work with cross-functional teams and all levels of management independently.

Responsibilities

• Develop exceptional analytical data products using both streaming and batch ingestion patterns on Google Cloud Platform with solid data warehouse principles.
• Build data pipelines to monitoring quality of data and performance of analytical models.
• Maintain the infrastructure of the data platform using terraform and continuously develop, evaluate, and deliver code using CI/CD.
• Collaborate with data analytics stakeholders to streamline the data acquisition, processing, and presentation process.
• Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards.
• Enhance and maintain the DevOps capabilities of the data platform.
• Continuously optimize and enhance existing data solutions (pipelines, products, infrastructure) for best performance, high security, low vulnerability, low costs, and high reliability.
• Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration and continuous deployment (CI/CD).
• Promptly address code quality issues using SonarQube, Checkmarx, Fossa, and Cycode throughout the development lifecycle.
• Perform any necessary data mapping, data lineage activities and document information flows.
• Monitor the production pipelines and provide production support by addressing production issues as per SLAs.
• Provide analysis of connected vehicle data to support new product developments and production vehicle improvements.
• Provide visibility to data quality/vehicle/feature issues and work with the business owners to fix the issues.
• Demonstrate technical knowledge and communication skills with the ability to advocate for well-designed solutions.
• Continuously enhance your domain knowledge of connected vehicle data, connected services and algorithms/models developed by data scientists within Ford.
• Stay current on the latest data engineering practices and contribute to the technical direction of the company while keeping a customer-centric approach.

Benefits

• Immediate medical, dental, vision and prescription drug coverage
• Flexible family care days, paid parental leave, new parent ramp-up programs, subsidized back-up child care and more
• Family building benefits including adoption and surrogacy expense reimbursement, fertility treatments, and more
• Vehicle discount program for employees and family members and management leases
• Tuition assistance
• Established and active employee resource groups
• Paid time off for individual and team community service
• A generous schedule of paid holidays, including the week between Christmas and New Year’s Day
• Paid time off and the option to purchase additional vacation time.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level