Partner with financial analysts to define and maintain the global view of company metrics, actively participating in discussions to support crucial commercial decisions.
Push the limits of dbt by developing scalable data models and writing custom macros to handle complex business logic, ensuring our code remains DRY and efficient.
Build end-to-end automations (using Python, Airflow, or n8n) to handle API integrations and reverse ETL processes that sync data back to operational systems.
Manage financial data pipelines by implementing rigorous monitoring, data quality tests, and freshness standards to guarantee trust in the numbers.

dbt mastery. You are comfortable writing custom macros, packages, and optimizing project structures.
Proficiency in SQL (performance tuning, readability) and at least one programming language, ideally Python.
Knowledge of some DataOps practices and tools including version control systems (e.g., Git), Docker, and CI/CD.
Experience with cloud infrastructure (ideally Google Cloud).
High degree of ownership.
Ability to prototype solutions quickly.
Technical aptitude and comfort with engineering-related discussions.
Excellent at communicating in both written and spoken Lithuanian and English.

Nice to have:

Gross salary: 3500
4800 EUR/month. Keep in mind that we are open to discuss a different salary based on your skills and competencies.
To support your professional growth and make you feel taken care of, we’ve put together an expansive benefit package. It covers learning, well-being, celebration, and much more — learn all about it here.

Analytics Engineer

Key skills