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Design and build production data engineering solutions to deliver reusable patterns using Google Cloud Platform (GCP) services: Big Query, Dataflow, DataForm, Astronomer, Data Fusion, DataProc, Cloud Composer/Air Flow, Cloud SQL, Compute Engine, Cloud Functions, Cloud Run, Artifact Registry, GCP APIs, Cloud build and App Engine, as well as real-time data streaming platforms like Apache Kafka, GCP Pub/Sub and Qlik Replicate. Collaborate with stakeholders and cross-functional teams to gather and define data requirements, ensuring alignment with business objectives. Design and implement batch, real-time streaming, scalable, and fault-tolerant solutions for data ingestion, processing, and storage for enterprise solutions in cloud-native tools. Perform necessary data mapping, impact analysis for changes, root cause analysis, data lineage activities, and document information flows. Develop and maintain documentation for data engineering processes, standards, and best practices, ensuring knowledge transfer and ease of system maintenance. Utilize GCP monitoring and logging tools to proactively identify and address performance bottlenecks and system failures. Provide production support by addressing production issues, per SLAs. Implement an enterprise data governance model and actively promote the concept of data - protection, sharing, reuse, quality, and standards to ensure the integrity and confidentiality of data. Work in an agile product team to deliver code frequently using Test Driven Development (TDD), continuous integration, and continuous deployment (CI/CD) by utilizing Tekton and Jenkin tools. Optimize data workflows for performance, reliability, and cost-effectiveness on the GCP infrastructure. Continuously enhance FMCC domain knowledge, stay current on the latest data engineering practices, and contribute to the company's technical direction while maintaining a customer-centric approach. EOE. Please apply online at: careers.ford.com recblid z81vqi3lfac08ra0lri0ihgjg2wges
Languages
- English
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