Tech Stack
AirflowApacheBigQueryCloudDockerETLGoogle Cloud PlatformPythonSQL
About the role
- Assist in reviewing and analyzing existing ETL solutions for migration to the new architecture
- Support the migration of batch and streaming data pipelines to the GCP Landing Zone
- Help build and maintain data transformations with dbt, supporting ELT pipelines in Snowflake
- Help with data jobs refactoring and mapping
- Assist in setting up and maintaining monitoring and alerting for data pipelines
- Contribute to migrating historical data to Iceberg tables with guidance from senior engineers
- Collaborate with senior engineers and stakeholders to understand requirements and implement solutions
- Participate in code reviews, team discussions, and technical planning to develop your skills
Requirements
- 0.5-1 years of experience in data engineering, data analytics, or software development
- Basic understanding of data warehouse concepts and ETL pipelines
- Good knowledge of SQL and willingness to learn Snowflake or similar data storage technologies
- Basic experience with Python for scripting or simple ETL tasks
- Experience with GCP platforms (BigQuery, GCS, Airflow, Dataflow, Dataproc, Pub/Sub)
- Understanding of version control (Git) and eagerness to learn CI/CD and IaC tools
- Degree in Computer Science, Data Engineering, or related field, or equivalent practical experience
- Strong communication and collaboration skills
- Upper-Intermediate English level
- Desirable: Basic exposure to streaming data pipelines and event-driven architectures
- Desirable: Familiarity with basic scripting and containerization tools (Bash, Docker)
- Desirable: Basic understanding of data lakehouse concepts (Iceberg tables)
- Desirable: Awareness of data transformation tools like dbt
- Desirable: Familiarity with AI-assisted tools like GitHub Copilot