Ford is hiring for Software Engineer!

Responsibilities of the Candidate:

• Interact with GDIA product lines and business partners to understand data engineering opportunities, tools, and needs.
• Collaborate with Data Engineers, Technical Anchors and Data Architecture to design and build templates, pipelines and data products including automation, transformation and curation using best practices
• Develop custom cloud solutions and pipelines with GCP native tools – Big Query, Dataproc, Data Fusion, Data Flow, DBT, Airflow DAGs and Terraform/Tekton
• Operationalize and automate data best practices: quality, auditable, timeliness and complete
• Participate in design reviews to accelerate the business and ensure scalability
• Leverages logging tools such as Dynatrace to support DevOps and debug production issues
• Follows software craftsmanship standards
• Pair program frequently to stay ahead of on the code base / tech stack.
• Coordinate reuse, architecture, and interoperability strategy.
• Foster DevOps CI/CD infrastructure and an Automated Testing mentality and capability. Champion continuous technical improvement for the platform, pursue tech debt opportunities.
• Help Product Owners understand our iterative development approach and focus on delivering a Minimum Viable Product through careful and deliberate prioritization.
• Grow technical capabilities / expertise and provide guidance to other members on the team

Requirements:

• Bachelor’s or Master’s degree in a Computer Science, Engineering or a related or related field of study
• Ability to work effectively across organizations, product teams and business partners.
• Knowledge Agile (Scrum) Methodology, experience in writing user stories
• Strong understating of Database concepts and experience with multiple database technologies – optimizing query and data processing performance.
• Full Stack Data Engineering Competency in a public cloud – Google Cloud or MS Azure or AWS
• Highly Proficient in SQL, Python, Java, Scala, or Go (or similar) - Experience programming engineering transformation in Python or a similar language
• Demonstrated ability to lead data engineering projects, design sessions and deliverables to successful completion
• Deep understanding of data service ecosystems including data warehousing, lakes, metadata, meshes, fabrics and AI/ML use cases.
• Effective Communication both internally (with team members) and externally (with stakeholders)
• Knowledge of Data Warehouse concepts – experience with Data Warehouse/ ETL processes
• Strong process discipline and thorough understating of IT processes (ISP, Data Security).
• Strong in Software Programming/Engineering with a good understanding of DevOps, GitHub etc