At Cloudera, we believe that data can make what is impossible today, possible tomorrow.
Senior Solutions Engineer
Location
Switzerland
Posted
7 days ago
Salary
0
Seniority
Senior
Job Description
Senior Solutions Engineer
Cloudera
• Own the technical sales process from introductory meetings (net new sales) through post-sales (customer satisfaction, upselling, and subscription renewals) for enterprise data, machine learning, and AI platform solutions. • Support the technical needs of customers including discovering new use cases for Cloudera’s technology, with a particular focus on Generative AI, predictive analytics, and enterprise MLOps. • Design solutions for your customers’ needs using Cloudera technologies, based on reference architectures and common patterns (e.g., Open Data Lakehouse, Retrieval-Augmented Generation / RAG, and end-to-end ML pipelines). • Demonstrate Cloudera products —including data engineering pipelines, model training/deployment workflows, and Generative AI features—in a way that inspires your customers to say “yes” to Cloudera. • Partner with your Account Managers to show your customers the true business and technical value of a Cloudera solution and drive successful sales. • Present product roadmap and vision —including state-of-the-art AI capabilities, hybrid MLOps, and secure data access—to inspire your customers to think bigger. • Interface with other Cloudera teams to ensure your customers hear one Cloudera voice. • Advocate for your customers’ needs to Product Management and Engineering. • Participate in external publicity and evangelism (conferences, meetups, webinars, blogs) focused on hybrid data platforms, modern data engineering, and enterprise AI. • Achieve goals aligned to a team target with annual sales expectations, as well as actively participate in knowledge exchange with peers and the wider community.
Job Requirements
- A minimum of 8 years experience in a customer-facing role, ideally in a pre-sales context focused on big data platforms, enterprise software, or advanced analytics platforms.
- The ability to create and give technical presentations and demonstrations that clearly translate complex data and AI concepts into strategic business value.
- Experience with some of the following technologies: Big Data, Data Warehousing, or Relational Databases (e.g., Apache Iceberg, Apache Spark, Hive, Hadoop ecosystem).
- AI & Machine Learning Ecosystems: Hands-on experience building, integrating, and deploying AI solutions using modern frameworks (e.g., PyTorch, Hugging Face, LangChain/LlamaIndex), vector databases, and MLOps tooling—with a deep understanding of GenAI architectures (RAG, fine-tuning, and model serving).
- One or more of the three major cloud service providers (AWS, Azure, or GCP).
- Formal cloud or AI/ML certifications are not required, but would be a great thing to have.
- Operations, Security, and Data Governance within the enterprise (including data privacy, compliance, and governance considerations for AI models and data assets).
- Unix or Linux environments and shell scripting.
- Experience gathering and understanding customer business requirements across traditional data engineering and modern AI applications.
- Excellent written and verbal communication skills.
- Strong problem-solving skills and an analytical mindset.
- A willingness to learn, a curiosity to discover , and a drive to make your customers successful in their digital and AI transformations.
- Four-year degree (Bachelor's) from an accredited university required (Computer Science, Data Science, Engineering, or related quantitative field preferred).
- Ability to travel domestically and internationally.
- This role is not eligible for immigration sponsorship.
Benefits
- Generous PTO Policy
- Support work life balance with Unplugged Days
- Flexible WFH Policy
- Mental & Physical Wellness programs
- Phone and Internet Reimbursement program
- Access to Continued Career Development
- Comprehensive Benefits and Competitive Packages
- Paid Volunteer Time
- Employee Resource Groups
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