Senior Solutions Engineer

Cloudera · Switzerland · posted today ago

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engineering machine-learning sales

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About this role

Business Area:

Sales Engineering

Seniority Level:

Mid-Senior level

Job Description:

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

Cloudera is the only hybrid data and AI platform company that large organizations trust to bring AI to their data anywhere it lives. Unlike other providers, Cloudera delivers a consistent cloud experience that converges public clouds, on-prem data centers, and the edge, leveraging a proven open-source foundation. As the pioneer in big data, Cloudera empowers businesses to apply AI and assert control over 100% of their data, in all forms, improving security, governance, and real-time and predictive insights. The world’s largest brands across all industries rely on Cloudera to transform decision-making and ultimately boost bottom lines, safeguard against threats, and save lives.

At Cloudera, our goal is to make everyone feel valued for their contributions to the company’s mission. We are looking for smart people who want to do remarkable things. We strive to build an environment of casual intensity where people enjoy coming to work every single day. We are currently seeking a customer-facing, hands-on technologist with a track record of success to join us in Switzerland.

As a Senior Solutions Engineer you will:

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.

We’re excited about you if you have:

A passion for using technology to make a difference to people and organisations. We'll supply some amazing tools to help you with this and you'll provide the connection to use cases (especially around data analytics, AI/ML, and modern automation), which make it real for your customers.
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.