Middle Data Engineer

We are looking for an engineer who does not just write ETL but shapes data infrastructure: from data lakes and cloud platforms to streaming systems and scalable pipelines.

• Design and implement pipelines for loading, cleaning, and transforming data in Data Lakes and Data Warehouses
• Actively monitor and optimize pipelines for performance and cost
• Configure deployment of pipelines and manage environment settings using IaC tools (Terraform) and CI/CD
• Implement data quality checks (e.g., Great Expectations, dbt tests) and ensure data integrity
• Communicate with stakeholders to clarify requirements and provide technical guidance and conduct code reviews for Junior engineers

• 2+ years practical experience in data engineering (ETL/ELT)
• Deep understanding of Data Warehousing concepts (Star/Snowflake Schema) and Data Lake principles (Medallion Architecture)
• Experience with Databricks (cluster management, notebooks), Azure Data Factory (pipelines, data flows) or Snowflake
• Proficiency in Python (OOP, functional programming) and strong SQL skills for complex transformations
• Practical experience with at least one major cloud platform (AWS, GCP, Azure) and its data services (e.g., Kinesis/Lambda, Dataflow/BigQuery, Synapse)
• Basic understanding of Infrastructure as Code (Terraform)

• Competitive compensation according to experience
• Impact on technology and architectural decisions
• An environment of strong engineers and architects
• Modern stack: Spark, Kafka, Snowflake, Databricks, Airflow, dbt, Docker
• Flexibility — remote-first and work-life balance
• International — global clients and multinational teams