Solutions Engineer at Cloudera helping customers deploy and utilize the CDP platform efficiently with technical expertise and customer service orientation.
Responsibilities
Create and deliver customer-centric solution designs, proposed architectures and business outcomes to all levels – developers, architects, CTO, and CIO.
Work with cross-functional teams including Sales, Marketing, Product Management, Services, Support, Training, and Engineering to share Cloudera’s Vision with customers.
Advise customers on use case patterns through discovery and requirements workshops.
Transform customer feedback into actionable product roadmap items.
Work with teammates and management to define technical selling strategy.
Participate within the Cloudera community, share evangelism activities (blogs, meetups, industry events), and contribute to internal and external knowledge repositories.
Requirements
5+ years of professional work experience in a similar position, selling solutions to business leaders and technical champions in the enterprise.
Strong experience with AI ecosystems (Agentic AI, Ethical AI solutions, Generative AI solutions and AI Development Tools like Cursor, CoPilot and Claude).
Demonstrated problem solving and analytical skills.
Experience in Solution Architecture/Engineering as a field of practice (an ability to listen to customer requirements, whiteboard and propose solution architectures, and be hands-on with the tech) to design, build, and demonstrate real business value.
Experience with the Apache Hadoop ecosystem (HDFS, YARN) and related components (Spark, Hive, Impala, Kudu, Solr, etc.) and can talk to the benefits of a centralized architecture for both data management and data access.
Experience with public cloud infrastructures (AWS, Azure, GCP, IBM Cloud, etc.).
Interest in achieving your public cloud certification.
Experience with the Linux OS and bare metal, VM, and distributed container platforms Kubernetes or OpenShift.
Some experience with specific private cloud infrastructures (Server Hardware, Storage, Networking).
Some experience of the formation of Data Lakes, principles of Data Warehousing, SQL and relational database patterns, and application integration.
Some knowledge of differentiators across the competitive landscape.
Some basic software development experience in Java, Scala or Python.
Some experience with Data Flow, Queues and Stream Processing (Nifi, Kafka, Flink, Spark) in enterprise applications.
Interest in Data Science and understand the difference between Data Engineering and Applied Science.
Passion about what you do and inspire people around you.
Bachelor’s Degree or equivalent experience in a Technical Field
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