Open Vacancies at LeverX - Join the team of talented software professionals

Middle Data Analyst | Work at LeverX

Written by Liza | Feb 5, 2026 10:50:13 AM

At LeverX, we have had the privilege of delivering over 1,500+ projects. 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 Middle 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 projects, 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 in 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:

  • 3–5 years in analytics/BI roles.
  • Strong hands-on Tableau (calcs, parameters, LODs, actions, performance tuning).
  • Proficient SQL (joins, window functions, CTEs).
  • Experience delivering on Data Warehouse and/or Lakehouse projects (star/snowflake modeling, ELT/ETL concepts).
  • Solid dashboard UX sense and data storytelling skills.
  • Clear communication and stakeholder management.
  • English for day-to-day work.

RESPONSIBILITIES:

  • Design, build, and maintain Tableau dashboards and data visualizations.
  • Gather and translate requirements into analytical specs; define metric formulas, grains, and filters.
  • Write efficient SQL to explore data, validate results, and prepare curated datasets.
  • Collaborate with Data Engineering on semantic layers and datasets sourced from DWH/Lakehouse platforms.
  • Ensure data quality via QA checks and concise documentation.
  • Present findings, run demos, and iterate based on stakeholder feedback.