Key Requirements:

• Minimum of 5 years of experience as a Data Engineer.
• Proficient in Databricks – daily work with this tool is crucial.
• Knowledge of: Python, PySpark, SQL, ETL Processing, AWS (S3, Docker).
• Basic knowledge of Azure.
• Experience with Infrastructure as Code (Terraform).
• Willingness to provide on-call support (additional pay): response within 30 minutes, support on a rotation basis with the team (one week of duty, three weeks off).

Nice to Have:

• Experience with tools: Kedro, Airbyte.
• Knowledge of ML and Medallion Architecture.
• Experience working with large volumes of data from various sources (Kafka, RDBMS, CDC, filesystem).

Responsibilities:

• Data ingestion and implementation of transformations using PySpark and SQL.
• Infrastructure management in AWS: S3, Docker, and Kubernetes.
• Work with Databricks: Unity Catalog, Workflows, jobs, data visualization in notebooks, code testing (unit and integration testing).
• Implementation of CI/CD solutions using CircleCI.
• Design and deploy solutions based on DataBricks architecture.