Associate Revenue & Artificial Intelligence Analyst, Personio

• Solid SQL skills — comfortable writing complex queries, CTEs, and transformations; basic Python (pandas, scripting, API calls) is a plus
• Exposure to dbt — you understand what a semantic layer is and why it matters; hands-on experience writing models, tests, and documentation is a plus
• Experience with at least one BI or data tool: Looker, Tableau, Hex, or equivalent; exposure to Snowflake or another cloud data warehouse is a plus
• Curiosity and a builder's instinct — you want to understand how things work, not just consume the output
• Clear communicator — able to explain a data problem to someone who doesn't work in data
• Interest or prior experience in AI tooling, LLMs, or workflow automation (n8n, Zapier, or Make)
• Experience in a B2B SaaS environment is a plus

Desirable

• This role requires 2 days per week in the office and is based in Munich, Berlin, or Dublin
• The Associate Analyst, Revenue & AI sits within the Customer Analytics department of Personio's broader Data & Systems team
• This role is built for someone early in their career who thinks like a builder as much as an analyst — someone who is as comfortable writing dbt models and shaping a semantic layer as they are turning data into a coherent narrative for a GTM leader
• This is not a traditional analytics role
• Day to day, you will work at the boundary of analytics and analytics engineering: owning the data models that power GTM reporting, helping define and maintain the semantic layer that makes our revenue data trustworthy and self-serve, and increasingly using AI tooling to automate the analytical workflows that today still take too long to do by hand
• You will sit close to Revenue Operations, GTM, and Analytics Engineering — learning the commercial context that makes good data work matter, and building the habits of a strong analytical partner early in your career
• Own and develop dbt models and contribute to the semantic layer — defining metrics, maintaining data dictionaries, and ensuring a single source of truth for GTM reporting
• Support analytical coverage of pipeline health, MRR/NRR, expansion signals, and regional performance using tools like Looker, Tableau, or Hex
• Contribute to LLM-powered workflows and automated reporting pipelines that replace manual analytical tasks
• Build strong working relationships with Sales, RevOps, and Finance, and proactively surface data quality issues and anomalies
• Manage your own changes in Git — branching, reviewing, and merging independently
• Work with CRM and RevOps datasets (Salesforce or HubSpot) to support pipeline and revenue reporting
• Contribute to self-serve AI tools that allow stakeholders to query data in natural language
• POSITION EXPECTATIONS:
• Platform & Semantic Layer
• Write, test, and maintain dbt models that power GTM and revenue reporting in Snowflake
• Contribute to metric definitions, documentation, and data dictionaries — ensuring that revenue numbers mean the same thing to everyone who uses them
• Manage your own changes in Git — branching, reviewing, and merging independently without relying on Analytics Engineering support
• Identify gaps in the reporting layer and propose pragmatic fixes
• Analytics & Stakeholder Work:
• Support end-to-end analytical coverage of pipeline health, MRR/NRR movements, expansion signals, and regional performance
• Help build and maintain dashboards and reports that stakeholders actually use and trust
• Work alongside the Senior Lead to prepare and present findings to GTM and Account Management leadership
• Learn to form and communicate a point of view on GTM data — not just "here is the number" but "here is what it means and what we should consider doing about it"
• AI & Automation:
• Contribute to LLM-powered workflows for automated insight generation, anomaly detection, and narrative summaries
• Help build and maintain automated reporting pipelines using n8n, Zapier, or Make
• Support the development of self-serve tools that allow stakeholders to query data in natural language
• Translate unstructured inputs — CRM notes, call transcripts, customer signals — into structured analytical inputs