Sales IS Manager - Sales data analyst H/F

Job Description

The Sales IS Manager is responsible for building, deploying, and maintaining the technical systems and infrastructure that power our Revenue Operations teams. This includes CRM (Salesforce) development, custom code (Apex) development, Lightning component configuration, system integrations, automation frameworks, data quality management, and increasingly, AI-driven solutions.

As the technical partner to Revenue Operations Managers, you transform architectural decisions into production-ready solutions that are reliable, measurable, documented, and maintainable.

You drive and support adoption by leading users’ enablement on process and tools.

You ensure that deployments go beyond proof-of-concepts to become scalable, long-term solutions that drive measurable business impact.

1. Technical Solution Design and Development

• Design, develop, test, and deploy custom Salesforce solutions leveraging Apex, Lightning Web Components (LWC), APIs, custom objects, and automation frameworks, ensuring scalable, maintainable, and high-performing business applications
• Develop and govern Salesforce automation and application architectures with a focus on error handling, bulk processing, recursion management, platform limits, performance, and sustainable maintainability
• Configure, maintain, and optimize CPQ product catalogs, pricing logic, approval workflows, and custom functionality to support scalable quote-to-cash operations and an efficient commercial process
• Integrate revenue technology platforms through APIs, ETL pipelines, and native connectors to enable seamless data exchange, process automation, and reporting consistency across the go-to-market ecosystem
• Lead data migration activities, including data extraction, cleansing, transformation, validation, and import/export processes, ensuring data integrity across Salesforce and connected business systems
• Design and implement data governance practices, including deduplication, enrichment, validation rules, and quality monitoring to ensure accurate, consistent, and reliable business data
• Define and enforce technical standards across sandbox and production environments, ensuring controlled deployments, effective testing, and reliable production releases

2. System Architecture and Technical Leadership

• Serve as technical lead for the Revenue Operations technology stack, ensuring alignment, scalability, and operational excellence across business systems
• Evaluate and recommend technology solutions and architectural approaches that optimize business value, scalability, maintainability, AI enablement, and operational efficiency while minimizing complexity and technical debt
• Define and enforce technical standards for application development, testing, deployment, environment management, and technical documentation, promoting maintainable solutions, knowledge sharing, and reliable platform operations

3. Documentation and Knowledge Transfer

• Create and maintain technical documentation, including system architectures, administration guides, operational procedures, and best-practice standards
• Deliver clear, actionable outputs and provide user training, knowledge transfer, and AI adoption guidance to support successful solution deployment and ongoing operations

AI-Driven Revenue Operations

• Design and deploy AI-powered workflows and agents that automate revenue processes, improve productivity, and enhance decision-making across the customer lifecycle
• Integrate LLM capabilities into business applications and automation frameworks while establishing governance for security, privacy, reliability, and operational scalability
• Establish and enforce AI guardrails, including human oversight, approval workflows, auditability, fallback mechanisms, cost controls, and data privacy standards to ensure safe and reliable production use
• Measure AI solution effectiveness through adoption, accuracy, operational impact, time savings, and business outcome metrics, continuously optimizing solutions beyond initial deployment
• Ensure data quality, structure, and governance standards are maintained to support reliable, scalable, and trustworthy AI capabilities

Qualifications

• CRM Expertise: Advanced configuration of Salesforce, including custom workflows, and data architecture – Salesforce Administrator, Platform App Builder, Platform Developer I/II, JavaScript Developer, or equivalent experience developing and integrating Salesforce solutions
• CPQ Expertise: Advanced configuration and administration of CPQ solutions, including product catalogs, pricing and discount strategies, approval workflows, quote generation, contract management, and commercial data architecture; experience with Salesforce CPQ/Revenue Cloud, DealHub, or equivalent quote-to-cash platforms
• Revenue Operations Ecosystem: Experience evaluating, implementing, and optimizing RevOps technologies, including CRM, sales engagement, marketing automation, customer success, and revenue intelligence platforms
• Automation Platforms: Proven hands-on experience with N8N, Make, or equivalent; strong understanding of error handling, data transformation, and workflow optimization
• API Integration: Experience leveraging APIs to connect revenue systems (CRM, ERP, CX, BI)
• Data Governance: Experience with data migrations, deduplication, enrichment, validation frameworks, and quality assurance
• AI and LLM Integration: Experience integrating AI and LLM technologies with CRM, analytics, and business applications
• AI Guardrails: Knowledge of production safeguards for AI—human validation, fallback mechanisms, cost monitoring, privacy/GDPR compliance, error tracking
• Technical Documentation: Strong ability to produce clear, structured technical documentation, architecture diagrams, and deployment guides
• Education: Bachelor's degree in engineering, computer science, or equivalent technical field (4-5 years post-secondary education)
• Experience: 3 to 5 years of technical experience in Revenue Operations, systems integration, or SaaS tool deployment

Additional Information

Desirable soft skills : 

• Business Acumen: Understanding of Revenue Operations processes and ability to design solutions that address real business problems
• Autonomy and Ownership: Self-directed approach to complex technical challenges with minimal supervision; ability to prioritize and multitask
• Communication and Teaching: Ability to translate technical concepts for non-technical stakeholders; strong presentation and knowledge-sharing skills
• Intellectual Rigor: Attention to detail, quality-focused mindset, commitment to building lasting solutions rather than quick fixes
• Adaptability: Exposure to diverse environments, technology stacks, and business models; comfort with continuous learning in a fast-evolving landscape. Ability to work cross-functionally with stakeholders in demanding environments