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Data EngineerNO C2CONLY W2 CONTRACT Position Description:The Cloud Center of Excellence is looking for a Data Engineer focused on problem solving to accelerate the adoption of the cloud first migration and optimization of the Google Cloud Platform. The successful candidate will work with multiple technical and non-technical teams to develop, document and evangelize data engineering best practices: define and create patterns to increase usability, acceptance and Google Cloud Platform enablement. This individual will exhibit deep technical knowledge, leverage agile principles and have a track record of developing full stack data engineering solutions to support customer needs and objectives: ingestion, transformation, curation and visualization.Skills Required:• Critical thinking skills to propose solutions, test, and make them a reality. • Full Stack Data Engineering Competency in a public cloud – Google, MS Azure, AWS • Highly Proficient in SQL • Python, Java, Scala, or Go (or similar) • Cloud native technologist (ideally Google Cloud Platform) • 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)Skills Preferred:• Extensive knowledge and understanding of Google Cloud Platform offerings, bundled services, especially those associated with data operations CloudConsole, BigQuery, DataFlow, DataFusion, PubSub / Kafka, Looker Studio, VertexAI • Experience with Teradata, Hadoop, Hive, Spark and other parts of Ford’s legacy data platform to support Google Cloud Platform migration. • 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 architectureExperience Required:• Drive delivery of efficient data engineering standards, templates, patterns and best practices by effectively using agile process methodology to define work, estimate effort, and measure results. • Define and complete full stack data engineering tasks: development, implementation, automation and monitoring. • Work with other departments such as the Data Factory Innovation Team and Architecture to actively participate in data engineering capabilities and proofs of concept to expand understanding, find technical limitations, explore options, and overcome challenges. • Create high quality, elegant data engineering best practices that focus on cloud-first, encapsulation, repeatability, automation and auditability. • Work as an individual contributor as well as part of a team building, maintaining and troubleshooting data pipelines.Contact