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 a wide variety of opportunities for you to accelerate your career potential as you help us define tomorrow's transportation.
Creating the future of smart mobility requires the highly intelligent use of data, metrics, and analytics.
That's where you can make an impact as part of our Global Data Insight & Analytics team.
We are the trusted advisers that enable Ford to clearly see 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.
**Required Skills**:
- Bachelor's degree in a Technical Field: Computer Science, Data Science, Computational Finance, Statistics, Economics and/or Mathematics: Masters Preferred.
- 5+ years of experience in data solution, pipeline, mart and/or warehouse development and delivery using agile development methodology.
- Critical thinking skills to propose solutions, test, and make them a reality.
- 2+ years of experience in a Data Engineering Competency on a public cloud - Google, MS Azure, AWS.
- 2+ years Integration and Configuration Scripting in Tekton and Terraform.
- 3+ years of experience writing complex SQL.
- 3+ years of experience writing data solutions in Python, Java, Scala or Go.
- Deep understanding of data service ecosystems including data warehouses, lakes, metadata, meshes, fabrics and analytical use cases.
- User experience advocacy through empathetic stakeholder relationship.
- Excellent Communication Skills, Verbal and Written, for both internal and external team members.
**Desired Skills**
- 2+ years Extensive knowledge and understanding of GCP offerings, bundled services, especially those associated with data operations Cloud Console, BigQuery, Data Flow, Data Fusion, PubSub / Kafka, Looker Studio and VertexAI.
- Experience with Teradata, Hadoop, Hive, Spark and other on-premise/legacy data solutions.
- Experience optimizing data solutions and data science/analytical workflows: re-coding/re-developing/re-factoring.
- Data Governance concepts including GDPR (General Data Protection Regulation), CCPA (California Consumer Protection Act), PoLP and how these can impact technical architecture.
- Design, Develop, and Implement data engineering solutions using standards, templates, patterns and best practices in the Google Cloud Platform:
- Full stack data engineering solutions utilizing both structured and unstructured data: development, ingestion, curation, implementation, deployment, automation and monitoring.
- Collaborates with the Data Factory Engineering Organization, Data Architecture, PEM, GDIA, Information Technology and Data Consumers to drive data engineering capabilities, product design and proof of concepts, MVPs, to expand understanding, define technical optimization, explore configurations and overcome challenges.
- Create high quality, elegant data engineering solutions that focus on cloud-first, encapsulation, repeatability, automation and auditability.
- Work as an individual contributor and part of a team to build, test, maintain and troubleshoot data solutions.
- Continuously integrates and deploys data solutions via CI/CD.
- Use of Test Driven Development and Code Pairing Practices.