At LeverX, we have had the privilege of delivering over 1,500 projects for various clients. With 20+ years in the market, our team of 2,200+ is strong, reliable, and always evolving: learning, growing, and striving for excellence.

We are looking for a Senior Data Analyst to join us. Let’s see if we are a good fit for each other!

what we offer:

• Projects in different domains: healthcare, manufacturing, e-commerce, fintech, etc.
• Projects for every taste: Startup products, enterprise solutions, research & development initiatives, and projects at the crossroads of SAP and the latest web technologies.
• Global clients based in Europe and the US, including Fortune 500 companies.
• Employment security: We hire for our team, not just a specific project. If your project ends, we will find you a new one.
• Healthy work atmosphere: On average, our employees stay with the company for 4+ years.
• Market-based compensation and regular performance reviews.
• Internal expert communities and courses.
• Perks to support your growth and well-being.

required skills:

• 5+ years of experience in data analytics, analytical engineering, or BI-related roles.
• Strong hands-on experience with analytical data modeling (dimensional modeling, facts and dimensions, star/snowflake schemas).
• Advanced SQL skills for transforming and shaping large datasets.
• Experience working with DWH/Lakehouse platforms (Snowflake, Databricks, BigQuery, Redshift, or similar).
• Ability to translate business requirements into clear and maintainable data models.
• Strong communication skills and ability to work directly with stakeholders.
• Professional working proficiency in English.

Responsibilities:

• Design and maintain analytics-focused data models that serve as the foundation for reporting and dashboards.
• Collaborate with data engineers and data architects to define modeling standards and data contracts.
• Validate data models against business processes and ensure consistency and correctness.
• Develop and optimize SQL transformations supporting analytical datasets.
• Support BI and self-service analytics by providing well-structured, analytics-ready data.
• Document data models, assumptions, and business logic for client teams.
• Mentor junior analysts on data modeling best practices.