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 Middle Analytics Engineer(ThoughtSpot Focus) to join us. Let’s see if we are a good fit for each other!
Location - Tbilisi
Level of English - B2
What we offer:
- Work with a modern lakehouse stack: Databricks, Delta Lake, dbt, orchestration tools, and cloud services
- A collaborative engineering culture with strong code review practices and knowledge sharing
- The opportunity to grow together with our Data Engineering practice and influence its development
- Participation in complex projects such as migrations, platform modernization, and large-scale data initiatives
- Flexible environment, autonomy in problem-solving, and support for professional development (certifications, courses, conferences)
Required skills:
- 3+ years in Data Engineering or BI/Analytics.
- Hands-on experience with ThoughtSpot: understanding of how to build Worksheets, TML files, and logical data models.
- Strong SQL skills: ability to write and debug complex analytical queries.
- Security knowledge: Experience managing users, groups, and SSO integrations (SAML/OIDC) in any BI or Data tool.
- Good communication skills to explain data concepts to non-technical users.
Nice-to-have skills:
- Experience with Modern Data Stack: Cloud Data Warehouse (Snowflake, Databricks, or BigQuery) + dbt
- Cloud vendors certificates
Responsibilities:
Experience building and maintaining ThoughtSpot Worksheets, Views, and the semantic layer (TML).
Strong understanding of data modeling (star schema) in Snowflake and/or Databricks.
Ability to optimize search experience (synonyms, keywords, drill paths).
Experience managing Access & Identity, including Auth Provider integrations and SSO.
Knowledge of data governance, including Row-Level Security (RLS) based on IdP groups and attributes.
Experience monitoring platform usage, query performance, and driving analytics adoption.