Director of Analytics; m​/f​/d

Location

Hybrid in Munich (minimum of 2 days a week from the office)

Usercentrics is a global leader in data privacy and privacy-led marketing solutions. We believe there is no need for a trade-off between growth and privacy compliance. Our vision is to unlock the potential of data privacy to empower a thriving digital ecosystem. We work with companies to create a healthy balance between data-driven business and privacy-led marketing for every size of enterprise.

Our customers build trust with their users through improved transparency and control to drastically improve marketing and monetization, while achieving full privacy compliance.

We are looking for a Director of Analytics to drive strategy, execution, and team leadership. This role owns the analytics vision at Usercentrics and is accountable for ensuring that data insights translate into tangible business impact, including clear ownership of analytics roadmap delivery and prioritization decisions. As the company grows, the data function must evolve from reporting and reactive analytics into a strategic partner that directly supports decision making and execution.

The Director of Analytics will lead this shift by managing a centralized analytics engineering function and a team of analysts aligned to business units through a dotted line reporting model, while ensuring consistency, alignment, and measurable impact across the organization.

• Define and own the analytics vision, positioning Analytics as a strategic partner that connects data, insights, and business action across the company.

• Build, scale, and structure the analytics organization, including a centralized analytics engineering function, data analysts, and data scientists aligned to business units through a dotted line model.

• Establish clear ownership boundaries and collaboration models between Data Science, Analytics, Analytics Engineering, and Platform teams.

• Define and standardize KPI frameworks, metric definitions, and reporting principles to ensure consistency, trust, and comparability across functions.

• Drive the adoption of self service analytics by improving data models, tooling, accessibility, and data literacy, reducing reliance on the Analytics team for basic insights.

• Ensure analytics outputs translate into concrete business actions by embedding insights into decision processes and supporting follow through and accountability.

• Act as the primary analytics partner to senior stakeholders in Product, Marketing, Operations, and Engineering, managing expectations and aligning priorities.

• Own the analytics engineering strategy, including data modeling principles, quality standards, governance practices, and scalable engineering workflows.

• Develop and oversee Marketing Analytics capabilities, covering measurement frameworks, attribution, and predictive use cases to support growth initiatives.

• Strengthen Product Analytics capabilities at scale, with a focus on reliable event tracking, data quality, consistent definitions, and self service usage by Product teams.

• Lead executive level communication and presentations, clearly articulating decisions, priorities, trade offs, and progress to senior leadership.

• Significant experience leading Analytics, BI, or Data functions in a SaaS or technology driven environment, with demonstrated ownership of strategy, execution, and team development.

• Strong hands on understanding of modern analytics stacks, including cloud data warehouses, analytics engineering workflows, semantic layers, and self service BI platforms.

• Proven ability to design and govern KPI frameworks, metric definitions, and reporting standards that are trusted by leadership and used to drive decisions.

• Experience building and scaling multi disciplinary analytics teams, including analytics engineers, data scientists, and analysts operating in an embedding model with strong business alignment.

• Solid background in Product and Marketing Analytics, ideally within a B2B or B2B2C SaaS context, with a clear understanding of growth drivers, customer lifecycle, and monetization levers.

• Experience leading Data Science initiatives, including experimentation, advanced analytics, and predictive modeling, with a focus on driving measurable business impact.

• Strong stakeholder management skills, with the ability to partner with senior leaders across Product, Marketing, Operations, Engineering, and Commercial functions.

• Excellent communication and storytelling skills, capable of translating complex data topics into clear narratives, decisions, and actions for executive audiences.

• Ability to operate at both strategic and execution levels, setting direction while remaining close enough to the work to unblock teams and establish best practices.

• Experience working in fast moving, ambiguous environments, balancing short term business demands with long term analytics strategy.

• Strong technical fluency across SQL based analytics, data modeling, and analytical programming, sufficient to set standards, review…