**Basic Qualifications:** + Bachelor’s or Master’s degree in a Computer Science, Engineering or a related or related field of study + 5+ Years - Ability to work effectively across organizations, product teams and business partners. + 5+ Years - Knowledge Agile (Scrum) Methodology, experience in writing user stories + 5+ Years - Strong understating of Database concepts and experience with multiple database technologies – optimizing query and data processing performance. + 5+ Years - Full Stack Data Engineering Competency in a public cloud – Google, MS Azure, AWS + Critical thinking skills to propose data solutions, test, and make them a reality. + 5+ Years - Highly Proficient in SQL, Python, Java, Scala, or Go (or similar) - Experience programming engineering transformation in Python or a similar language. + 5+ Years Demonstrated ability to lead data engineering projects, design sessions and deliverables to successful completion. + Cloud native technologist + Deep understanding of data service ecosystems including data warehousing, lakes, metadata, meshes, fabrics and AI/ML use cases. + User experience advocacy through empathetic stakeholder relationship. + 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). **Responsibilities:** + Interact with GDIA product lines and business partners to understand data engineering opportunities, tooling and needs. + Collaborate with Data Engineering 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 – Data Prep, Data Fusion, Data Flow, DBT and Big Query + Operationalize and automate data best practices: quality, auditable, timeliness and complete + Participate in design reviews to accelerate the business and ensure scalability + Work with Data Engineering and Architecture and Data Platform Engineering to implement strategic solutions + Advise and direct team members and business partners on Ford standards and processes. **Preferred Qualifications:** + Excellent communication, collaboration and influence skills; ability to energize a team. + Knowledge of data, software and architecture operations, data engineering and data management standards, governance and quality + Hands on experience in Python using libraries like NumPy, Pandas, etc. + Extensive knowledge and understanding of GCP offerings, bundled services, especially those associated with data operations Cloud Console, BigQuery, DataFlow, DataFusion, PubSub / Kafka, Looker Studio, VertexAI + Experience with Teradata, Hadoop, Hive, Spark and other parts of legacy data platform + Experience with recoding, re-developing and optimizing data operations, data science and analytical workflows and products. + Data Governance concepts including GDPR (General Data Protection Regulation), CCPA (California Consumer Protection Act), PoLP and how these can impact technical architecture **Requisition ID** : 44631