What you will be doing:
- Building ETL processes: developing and configuring pipelines for collecting and transforming data from various sources;
- Working with a modern transformation stack: learning and applying DBT to convert "raw" data into clean analytical data marts;
- Data orchestration: setting up and supporting workflows (pipelines) in Dagster to ensure data in reports is updated on time and without failures;
- Managing storage: working with Postgres and the high-performance columnar database Clickhouse to ensure the speed of report operation;
- Visualizing insights: developing interactive BI reports in Apache Superset to help the business make data-driven decisions;
- Optimizing queries: analyzing and accelerating heavy queries to improve the performance of the entire reporting system.
What we expect from you:
- SQL: confident command of the language (complex queries, aggregate functions, understanding of query optimization principles);
- Databases: understanding of relational database structures (specifically PostgreSQL) and general principles of building analytical data warehouses;
- Python: basic knowledge of the language, ability to write scripts for data processing and automation of simple tasks;
- Analytical mindset: ability to work with large datasets, identify patterns, and structure information.
Desirable experience:
- BI tools: experience in creating dashboards in Apache Superset, Tableau, Power BI, or similar systems;
- ETL/ELT: understanding of data extraction, transformation, and loading concepts;
- Data architecture: understanding the difference between OLTP and OLAP systems (e.g., why Clickhouse is used for analytics);
- Modern stack: interest in DBT (Data Build Tool) or data orchestrators (Airflow, Dagster).
We offer:
Fixed-term employment contract for 3 months, 5/2 schedule, no more than 30 hours per week, remote/office/hybrid.
We consider students from any universities, any form of study, including part-time, including Master's programs, for internships.
