Senior Analyst, Personio

• 5+ years in analytics engineering, analytics, or a hybrid of both — you have done both the building and the analysis, not just one side
• Expert-level dbt: you have built models from raw source data, written tests, managed documentation, and understand lineage end-to-end — not just maintained existing models
• Strong SQL: complex queries, performance optimization, ability to work across a Snowflake-based data warehouse without hand-holding
• Analytical rigour: you structure ambiguous problems into hypotheses, identify the right metrics, and produce outputs that lead to decisions — not more questions
• Clear communicator: you translate data into plain language for non-technical stakeholders, present confidently, and write documentation that people actually use
• Experience with BI tooling (HEX, Tableau, Looker, or equivalent) for building stakeholder-facing dashboards and reporting
• Comfortable with Git and version-controlled codebases as a daily practice
• High ownership: you diagnose root causes, drive work independently, and don't wait to be told what matters next

Desirable

• We empower Personio's decision-making with reliable data and strategic insights, while improving productivity through scalable infrastructure and automation
• Be part of our transformative journey in HR technology, where your contributions shape how a leading people management platform understands its own workforce
• The Senior Analyst — PWI sits within the Data, Systems & AI department and partners closely with the People & Workplace Intelligence (PWI) function
• This role combines two capabilities that are most powerful together: building the data foundations that make reliable analysis possible, and delivering the analysis itself. You own the infrastructure — writing dbt models from raw sources — and you own the insight: turning that data into clear recommendations for People leadership and partners
• You will work closely with PBPs and People leadership to connect people data sources — HRIS, absence and attendance systems, and others — and enable a self-serve analytics capability across the people domain
• Build and own dbt models end-to-end — from raw source ingestion through to staging, intermediate, and reporting layers — for the PWI domain, covering HRIS, headcount, absence, attendance, and adjacent people data sources
• Design and maintain scalable warehouse schemas in Snowflake, with clear data lineage, documentation, and version-controlled code (Git)
• Define, document, and steward metric definitions and the semantic layer for people data, ensuring reliable KPI logic and metric consistency across the domain
• Implement data quality testing, monitoring, and alerting so that data issues are caught early and fixed proactively — not discovered by stakeholders
• Deliver structured analysis on headcount, attrition, absence and attendance, org design, manager effectiveness, and compensation for PBPs and PWI leadership — forming clear hypotheses and producing decision-ready outputs, not just data dumps
• Build and maintain intuitive dashboards and reporting that allow stakeholders to self-serve on day-to-day questions without requiring analyst involvement
• Support MBR and QBR cycles with data storytelling: own the narrative, not just the numbers
• Partner with PBPs to diagnose root-cause data gaps, translate urgent business needs into analytical deliverables, and systematically improve the quality of people data over time
• Act as the embedded analytical partner for the PWI function — showing up proactively, anticipating needs, and flagging risks before they escalate
• Present findings directly to People leadership with confident, prescriptive recommendations
• Enable PBPs to work more independently with data through documentation, self-serve tools, and direct coaching