Data Analyst

Xebia is a global, award-winning, AI-first consulting, software engineering, and training company. It helps organizations turn AI strategy into production-ready solutions. The company operates globally with client-facing teams in the US and Europe, nearshore capacity in Poland and Latin America, and an offshore hub in India. Xebia combines local expertise with global reach through a sophisticated hybrid delivery model.

• At least 3 years of experience in a similar role
• Advanced SQL skills, including writing and optimizing complex queries
• Strong experience with data analysis, data quality, data modeling, data profiling, and documentation
• Proven ability to analyze large, complex datasets and translate them into insights
• Experience with data validation, data quality checks, and ensuring data integrity
• Strong understanding of data discovery, data profiling, and source analysis
• Familiarity with logical and physical data models, semantic layers
• Ability to collaborate effectively with technical (engineering) and business teams
• Detail-oriented mindset with a strong focus on data quality and consistency
• Upper intermediate/Advanced English (B2/C1)
• Practical experience using AI-powered assistants (e.g., ChatGPT, Claude, Copilot Chat) to improve productivity, quality, or decision-making in analysis and software delivery

• Analyze complex datasets to identify trends, patterns, and insights
• Write and optimize complex SQL queries to support data analysis and product needs
• Ensure data quality through validation, testing, and defining quality checks
• Profile and explore new and existing data sources to assess structure, usability, and reliability
• Conduct data investigations to understand lineage, inconsistencies, and anomalies
• Document data flows, business logic, constraints, and processes to build organizational knowledge
• Collaborate with Data Engineering, Product, and business stakeholders on data-related initiatives
• Contribute to the development of data models (logical & physical), including semantic layers and curated datasets
• Recommend improvements to data structures for performance, scalability, and usability
• Build and maintain business and technical metadata such as glossary, KPIs, and data definitions
• Support development and enrichment of the data catalogue across internal and external sources
• Assist Product Managers in delivering outcomes within the product area
• Support business teams during UAT and post-production with analysis and data-related queries
• Partner with engineering teams to inform system and data design decisions