Data Engineer
Our ongoing projects are in full swing, and we’re dedicated to delivering top-notch work without being tied down by a strict corporate structure.
We are looking for an experienced Data Engineer to help develop and maintain our data infrastructure. In this role, you will work with large-scale datasets, build and optimize data marts, maintain and improve data pipelines, and contribute to the design and evolution of our data warehouse architecture.
What you will be doing:
- Designing data models for new entities: defining schemas, relationships, and field specifications;
- Working closely with the Analytics team to align on data requirements and business logic;
- Building and maintaining reliable ETL/ELT pipelines for data extraction, transformation, and loading;
- Writing and optimizing SQL queries for data warehouse tables and data marts;
- Resolving data ingestion issues, including debugging, validation, and data recovery;
- Creating data marts and configuring table structures, TTL, indexes, and compression settings;
- Managing data access controls, including setting up permissions and designing secure access models.
What we want to see:
- 4+ years of experience as a Data Engineer or in a similar role;
- Strong SQL proficiency, including window functions, CTEs, and query optimization;
- Solid Python skills (Pandas, Airflow operators, and data processing scripts);
- Hands-on experience with Apache Airflow 2, including writing DAGs, debugging, and monitoring;
- Deep understanding of data orchestration principles;
- Experience with ClickHouse (MergeTree family tables, TTL, indexes, JOINs, and handling large-scale aggregations);
- Familiarity with web scraping techniques and tools;
- Experience working with S3, BigQuery, and other data storage or analytics solutions.
Additional Cool-to-Have Qualifications:
- Experience working closely with analytics teams and understanding their needs;
- Hands-on experience with Liquibase;
- Experience with data migration between systems (e.g., PostgreSQL to ClickHouse, S3 to BigQuery);
- Familiarity with CI/CD practices in the context of Airflow, dbt, or GitLab CI;
- Good understanding of data modeling methodologies such as Data Vault, Star Schema, and Snowflake Schema.
Growth and development
Our project is actively growing, as well as the team that creates it. We invest in the growth of each specialist and regularly review salaries based on performance. Moreover, we have a promotion system that allows specialists to showcase their talents in more responsible positions.
Comfortable conditions
You can choose various work types: hybrid or office. Also we have flexible hours with the option of taking days off.
Care for employees
We offer sick days without salary loss, assistance in difficult life situations, no bureaucratic nightmares and processes for the sake of processes.
