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# Middle Data Analyst

- **Company:** The Lever Group LLC
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Information Engineering, Extract Transform Load (ETL), Data Presentation, Data Visualization, Data Warehousing, Performance Tuning, SAP (Applications), SQL Databases, Tableau (Software), Snowflake, Web Technologies
- **Published:** June 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=2f32a2b6e98371db

## About the Role

Do you have experience in Tableau?, * 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.

## Description

* 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., * 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.


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