Data Engineer

We are looking for a Data Engineer to join our team and build reliable data pipelines for current and upcoming analytics projects. You will work with Python, Apache Airflow, ClickHouse, PostgreSQL, AWS S3, and Nextcloud to deliver clean, trusted datasets for BI/reporting and operational dashboards. In addition to core ETL/ELT work, we need a strong agentic data engineering mindset: automating routine DE tasks (pipeline scaffolding, data checks, incident triage, and documentation) with AI-assisted workflows under clear quality and safety guardrails.

Requirements:

• 3+ years of hands-on Data Engineering experience
• Strong Python skills for data pipelines and automation
• Solid experience with Apache Airflow (DAG design, scheduling, monitoring, troubleshooting)
• Advanced SQL and practical experience with ClickHouse and/or PostgreSQL
• Experience with AWS S3, Nextcloud, and data ingestion from files/APIs
• Understanding of ETL/ELT patterns, incremental loads, idempotency, and partitioning
• Experience with data quality checks, logging, and alerting
• Experience (or strong practical interest) in agentic/AI-assisted engineering for automating repetitive workflows
• Good Git workflow and collaboration skills
• English: intermediate+ (written and spoken)

Responsibilities:

• Design, develop, and maintain Airflow DAGs for batch data pipelines
• Build and improve data ingestion from S3, Nextcloud, APIs, and relational databases
• Model and optimize tables in ClickHouse for performance and analytics use cases
• Implement and maintain data quality/reconciliation checks
• Monitor pipeline health, troubleshoot production issues, and improve reliability
• Collaborate with analysts/BI stakeholders to deliver marts and reporting datasets