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Veeam Software, the Data and AI Trust Company, is expanding its People Analytics function and seeking a People Data Analyst to drive the next phase of workforce intelligence. Reporting to the Director of People Transformation and Analytics, you will own analytical projects end-to-end, from data preparation through stakeholder delivery, working across the full employee lifecycle including headcount, attrition, retention, internal mobility, performance, compensation, and engagement.
You will build analytics-ready datasets using SQL, Python, and Databricks, transforming and modeling people data to support reliable, scalable analytics. You'll partner with Data Engineering and data warehouse teams to integrate new data sources from Workday and Greenhouse, defining data requirements and curating analytical datasets. You'll design, develop, and maintain analytical solutions including Tableau and Databricks dashboards, AI-powered applications, conversational interfaces, and automated insight delivery through platforms like Microsoft Teams and email.
Key responsibilities include delivering operational people intelligence by tracking workforce metrics; leading analytical projects covering attrition root causes, promotion equity, workforce segmentation, and onboarding effectiveness; proactively identifying workforce trends and emerging risks; and collaborating directly with People & Culture leaders and business stakeholders to translate complex findings into actionable recommendations. You'll ensure data quality, consistency, and governance while protecting sensitive employee information through appropriate privacy and access controls. You'll also leverage AI tools to improve analytical workflows and contribute to developing AI-enabled people analytics capabilities.
Requirements:
- 3–5 years of experience in data analytics, business intelligence, or analytics engineering, with demonstrated ownership of analytical projects from start to finish
- Strong SQL proficiency and working knowledge of Python, including experience querying large datasets, transforming data, and developing scalable analytical solutions
- Hands-on experience with modern cloud data platforms such as Databricks or Snowflake (Databricks strongly preferred)
- Experience in analytics data modeling, including designing and building curated, analysis-ready datasets and tables for reporting and downstream analytical applications
- Proven ability to build production-ready dashboards and BI solutions using Tableau, Databricks AI/BI Dashboards, Power BI, or comparable platforms, with understanding of calculated fields, performance optimization, and governance
- Strong data visualization and storytelling skills, with ability to communicate complex analytical findings clearly and tailor insights to different audiences
- Excellent stakeholder management, consulting, and communication skills, including ability to translate ambiguous business questions into practical analytical solutions
- Strong critical thinking, problem-solving, and organizational skills, with ability to work independently and proactively identify opportunities for improvement
- Working knowledge of HR, recruiting, or workforce data, including understanding of key people metrics and importance of data privacy and confidentiality
- Demonstrated adoption of AI tools in analytical workflows, including ability to evaluate effectiveness, validate outputs, and identify opportunities for efficiency and innovation
- Fluency in English, both written and verbal, with ability to collaborate effectively across global teams
Desirable qualifications:
- Experience with HR and recruiting platforms such as Workday, Greenhouse, Qualtrics, or comparable systems
- Experience developing AI-powered or data-driven applications, conversational analytics interfaces, Databricks Apps, or automated insight delivery solutions
- Knowledge of statistical analysis or predictive modeling, including attrition risk analysis, workforce forecasting, or anomaly detection
- Previous exposure to workforce planning, HR analytics, organizational effectiveness, data governance, or security models for sensitive information
