Sales Specialist, Open Source Software

Job not on LinkedIn

🔥 15 minutes ago

🗣️🇩🇪 German Required

🗣️🇫🇷 French Required

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Logo of Stackable

Stackable

11 - 50 employees

Founded 2020

☁️ SaaS

🏢 Enterprise

🤝 B2B

💰 Seed on 2022-02

SaaS • Enterprise • B2B

Stackable is a modular, Kubernetes-native open source data platform designed to assemble and run curated open-source data applications (e. g. , Apache Kafka, OpenSearch, Trino, Apache Spark) into enterprise-class architectures. It supports Data Lakehouses, Event Streaming, Data Mesh patterns, and machine learning workloads; runs on-premises, in cloud or hybrid environments; and is offered as open-source software with commercial subscription and managed-service options. Stackable emphasizes data sovereignty, interoperability, and European standards compliance.

📋 Description

• New customer acquisition and expansion of existing customer relationships in the enterprise segment • Managing complex B2B sales cycles from qualification to contract closing • Positioning our data platform as a strategic solution for data analytics, AI/ML and modern data architectures • Collaborating with partners to develop and execute a successful go-to-market strategy

🎯 Requirements

• Minimum 5–7 years’ experience in B2B sales of enterprise software in the data and analytics domain • Understanding of modern data technologies • Experience with open-source software and its business models, particularly in the context of digital sovereignty • Fluent German, French and English, both written and spoken (C1 or higher) • Strong network in the financial sector (banks, insurance, FinTech) in Switzerland and/or France desirable • Startup or scale-up experience with a hands-on mentality • Knowledge of big data technologies and data engineering concepts • Familiarity with cloud platforms and Kubernetes

🏖️ Benefits

• 100% remote work with flexible hours • Competitive compensation package with variable, performance-based pay • Direct influence on product development and go-to-market strategy • Flat hierarchies and short decision-making paths

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