RevOps Engineer (Data & BI)

Location: On-site in Berlin, Germany. Work takes place in person at the Berlin office; the workday starts at 8:30.

Salary: €65,000–€80,000 per year, plus equity.

Company

hirify.global builds a secure, model-agnostic AI platform that brings leading AI models, chat, agents, integrations, workflows, and APIs to organizations.

What you will do

• Architect shared commercial data models and BI by connecting CRM, billing, product, and go-to-market data.
• Build and maintain revenue tracking, billing reconciliation, lifecycle metrics, and a reliable source of truth.
• Support commercial planning, quotas, compensation structures, forecasting, and account development with clean data models.
• Investigate growth drivers and commercial questions with Sales, Customer Success, Marketing, Partnerships, Finance, and Engineering.
• Design lead, sales, customer success, renewal, and expansion handoffs with clean CRM workflows.
• Use AI agents, automation tools, and CRM integrations to eliminate repetitive operational work.

Requirements

• Strong hands-on SQL skills and experience combining messy data sources into resilient relational models.
• Engineering mindset with experience building sustainable workflows, testing edge cases, validating outputs, and documenting data work.
• Understanding of B2B SaaS mechanics and the commercial impact of data.
• Practical experience with CRM systems such as HubSpot, billing data, and automation tools.
• Hands-on experience using AI and automation to solve operational problems.
• Ability to translate ambiguous commercial questions into technical requirements and communicate findings clearly.

Culture & Benefits

• Calm, solution-focused working environment with ambitious execution and strong ownership.
• In-person collaboration from the Berlin office.
• Catered lunch and dinner at the office.
• Gym membership and coaching resources.
• Transparent salaries tied to levels; all roles include equity.
• Most hiring processes are completed within two weeks.

Hiring process

• Applicants are encouraged to provide an example of a data model, analysis, or workflow automation, explaining the problem, implementation, and learnings.
• The expected level and salary range are clarified early in the process.