Senior Sales Analyst

About the role

Join the Global Sales Analytics team to influence how AutoScout24 tracks revenue and makes commercial decisions. You will serve as a strategic partner to leadership, managing revenue analytics products and ensuring data consistency across our international markets. In this capacity, you will own the definition and evolution of key revenue metrics that guide the commercial strategy of the business. Your work will directly impact how the company understands its performance and allocates resources based on analytical insight. You are expected to act as an owner of complex analytics initiatives from conception through production deployment. The role requires a proactive approach to identifying opportunities for improvement in how sales data is structured and consumed. You will translate ambiguous business questions into precise analytical deliverables that drive measurable impact.

Key facts

What you'll do

• Manage and upgrade core revenue analytics products used for performance tracking and strategic planning, ensuring they meet evolving business needs.
• Create and support scalable data models and reporting structures that can adapt to growth and changing requirements.
• Oversee the reliability of the analytics ecosystem, including data pipelines and validation processes, to maintain stakeholder trust.
• Collaborate with Data Engineering to refine data architecture and improve reporting automation, reducing manual intervention and errors.
• Standardize KPI definitions and reporting methods across different regions to ensure alignment and comparability of results.
• Perform deep-dive analyses to uncover commercial risks and growth potential, providing clear recommendations to guide action.
• Assist with major business projects like pricing model shifts, CRM updates, and new market entries, contributing analytical depth.
• Utilize AI tools to increase the speed and efficiency of analytical workflows, leveraging technology to augment productivity.
• Develop and maintain documentation for analytical products and processes to support knowledge transfer and continuity.
• Partner with commercial stakeholders to gather requirements and ensure analytical solutions address real business problems.
• Monitor key performance indicators on an ongoing basis to detect anomalies and trends that require investigation.
• Lead data quality initiatives to improve the accuracy, completeness, and consistency of sales-related datasets.
• Mentor junior analysts on best practices for data analysis, visualization, and communication techniques.
• Contribute to the continuous improvement of the analytics roadmap by proposing enhancements based on user feedback.

Requirements

• 6+ years of professional experience in Business Intelligence, Revenue Operations, or Analytics, demonstrating a track record of impact.
• Proficiency in SQL and Python, including the use of AI tools for problem solving and automation, to develop efficient and maintainable solutions.
• Practical experience with pipeline management and workflow orchestration tools like Airflow, ensuring robust and reliable data processing.
• Proven ability to build and maintain analytical data products and reporting layers that support decision-making at scale.
• Experience working with BI platforms such as Looker, Power BI, Tableau, or QuickSight, creating intuitive and insightful visualizations.
• Ability to communicate complex data insights to influence commercial decision-making, bridging the gap between technical and business audiences.
• Strong attention to detail and a methodical approach to analysis, ensuring that conclusions are based on solid evidence.
• Comfort working in a fast-paced environment where priorities can change and adaptability is essential for success.
• A commitment to data governance and compliance, understanding the importance of security and privacy in analytical practices.
• Willingness to collaborate closely with cross-functional teams, including sales, marketing, and product management, to achieve shared objectives.

Nice to have

• A strong engineering mindset focused on data reliability, scalability, and maintainability, leading to sustainable analytical solutions.
• Experience investigating and resolving data quality issues across multiple integrated systems, ensuring consistency and trust in data outputs.
• A balance of technical expertise and business acumen, allowing for effective communication regarding both strategy and data architecture.
• A critical approach to data that challenges assumptions and prioritizes high-quality, trustworthy output that stakeholders can rely on.
• Understanding of how to integrate human judgment with AI-driven analytical processes, optimizing the synergy between technology and expertise.
• Familiarity with the automotive market and digital sales ecosystems, providing context that enhances the relevance of analytical insights.
• Experience working in a global environment with multiple stakeholders, navigating cultural and regional differences effectively.
• Exposure to machine learning techniques or advanced statistical methods, applying these concepts where they add value to business problems.
• Participation in open source projects or contributions to the analytics community, demonstrating a commitment to knowledge sharing.
• A portfolio of successful analytics initiatives that have driven measurable business outcomes in previous roles.

Practical notes

The position is based in Munich, Germany, and requires the ability to work from this location on a full-time basis. There may be requirements for occasional travel within Europe to engage with regional teams and stakeholders. Candidates must be eligible to work in Germany without restrictions, and any necessary sponsorship information should be discussed during the application process if applicable. The role demands a significant time commitment during standard business hours, with flexibility to address urgent analytical requests when necessary. Applicants should be prepared to manage multiple priorities and meet firm deadlines for reporting and project delivery. The successful candidate will be expected to adhere to the company's code of conduct and data handling policies at all times.