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It is an Engineering and Operations position for our strategic visualization platforms in on-premises, Software-as-a-Service (SaaS), and Google Cloud instances. Evaluate, engineer, test, release and manage existing and upcoming analytics technologies for Enterprise consumption in Google Cloud, SaaS, and on-prem environments.
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This role will join a team developing the next generation of autonomous driving solutions drawing on state of the art technologies including big data analytics, cloud, agile and automation, for solving business problems in the automotive and next-gen mobility industry.
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Provide thought leadership on Salesforce Marketing Cloud and omni-channel digital marketing best practices. The ideal candidate will possess extensive hands-on experience with Salesforce Marketing Cloud, demonstrating expertise in campaign management, customer journey personalization, data analysis, and marketing automation optimization.
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ResponsibilitiesProvide thought leadership on Salesforce Marketing Cloud and omni-channel digital marketing best practices. Design, build, and execute marketing campaigns utilizing Salesforce Marketing Cloud.
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Demonstrable experience in Salesforce Marketing Cloud administration, configuration, and development. Keep abreast of industry trends, updates, and best practices in marketing automation and Salesforce Marketing Cloud functionalities.
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Our analytics platforms include Looker, Qlik Sense, Alteryx, WebFOCUS, and Power BI. The selected candidate will also assist with the management of cloud-based platforms and the development of tools to automate processes used to operate these platforms.
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Technical expertise designing and implementing systems on Google Cloud, leveraging modern application infrastructure and DevSecOps. Ford Motor Company was built on the belief that freedom of movement drives human progress.
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Applicants are invited to apply from the following areas: Computer architecture, computer systems, cloud computing, edge computing, machine learning, hardware security, mixed signal integrated circuits, RFIC's, autonomous systems, an embedded systems for the loT in automotive nd health care applications.
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Navigate through extensive datasets using tools such as Google Analytics, Adobe Analytics, Salesforce, Google Ads Data Hub, and Amazon Marketing Cloud, transforming data into actionable insights through compelling storytelling.
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Implement Cloud based solutions based on various GCP services and technologies such as BigQuery, Dataflow, Dataproc, Bigtable, Dataform, Data fusion, cloud spanner, Cloud SQL, Cloud functions and Cloud scheduler.
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Lead the design and implementation of complex cloud solutions using Microsoft Azure, focusing on integration with Databricks and Azure Data Factory. As a lead cloud engineer for Azure, you will be responsible for designing and implementing scalable, high-performance data engineering solutions using Azure Databricks and Azure Data Factory.
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Configure and customize the Salesforce Marketing Cloud to meet complex business requirements, enhancing marketing automation processes. We are in search of a Salesforce Marketing Cloud Product Expert with a strong product, technical, marketing and analytical background.
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Lead data analysis required to troubleshoot data related technical issues and resolution Deploy and automate Machine Learning Models in a data environment (e.g., SQL server, Cloud platform, on-premise servers and machines) and include workflow orchestration, scheduling and implementing advanced data processing and data delivery tools like docker for containerization.
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From rapid deployments to entire transformations, you'll deliver integrated, payroll, cloud-based HR and financial management solutions that put organizations on the fast track to a better way to work.
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15+ years related working experience managing people/teams in Manufacturing IT, including advanced technology skills such as IIOT, AR/VR, AI, cloud and other Industrie x. Build high-performing software organization required to execute the mission, leverage cloud/SaaS, modern software development practices, and hardening our data architecture required throughout intelligent and EV production lifecycle.
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