Data Engineer

We are looking for an experienced Data Engineer to design and implement scalable data pipelines, own core storage layers, and help build the foundations of a modern DataOps lifecycle.

Job requirements 3+ years of professional experience in Data Engineering / DWH development. Strong SQL expertise and solid Python skills (pandas, pyarrow). Production experience with Apache Airflow (production DAGs, scheduling, operators). Hands‑on work with PostgreSQL (schema design, migrations, partitioning) and ClickHouse (MergeTree engines, materialized views, performance tuning). Experience with Data warehouse design — layered architecture, data modelling, denormalisation. Experience integrating REST APIs and third-party data sources Experience with Docker / Docker Compose — containerised services and multi-service environments Fluency in English.

Nice to Have: Experience with Apache Superset (RLS, dashboard layer). Familiarity with AI/LLM tooling for data (NL-to-SQL, vector databases). Experience in the Fintech field: FX, brokerage, CRM/BO systems. Experience with multi-tenant data architectures. Job responsibilities Design, build, and maintain ETL/ELT pipelines rom multiple product datasources. Model and optimise data structures in ClickHouse (views, engines, schema evolution). Orchestrate workflows using Apache AirflowCollaborate with BI teams (Superset) and backend teams (FastAPI/Python) to build reliable data products. Contribute to architectural decisions. Collaborate closely with product managers, BI developers, and DevOps to deliver data products end‑to‑end.

Job benefits ● Competitive and Attractive Pay. ● Flexible hours for a better work-life balance. ● Work your way: Hybrid flexibility to fit your life. ● 21 vacation + 7 no-questions-asked sick days per year. ● Career growth: Continuous Development & Performance Reviews.