Data Engineer GCP

The project focuses on building and enhancing a data platform on Google Cloud Platform. The team integrates data from multiple GCP-based data assets, transforms it into usable formats, and delivers high-quality data pipelines for downstream analytics and business use cases. The environment is cloud-native and leverages modern data engineering practices including CI/CD, orchestration, and scalable data processing frameworks.

• Strong experience with Google Cloud Platform
• Very good knowledge of Python and SQL
• Hands-on experience with BigQuery and Cloud Storage
• Experience with Apache Airflow or Cloud Composer
• Experience in building and maintaining data pipelines in production environments
• Strong understanding of data modeling (data lake, DWH, star schema, Snowflake)
• Experience with CI/CD and pipeline orchestration
• Ability to design scalable and maintainable data solutions
• Experience with data quality, testing, and observability practices

Nice to have:

• Experience with PySpark
• Knowledge of Spark and/or Hadoop ecosystems
• Experience with streaming or big data processing solutions
• Background in backend services development (Python)

• Design and develop scalable data pipelines on Google Cloud Platform using Python and SQL
• Integrate data from various GCP data sources such as BigQuery and Cloud Storage (buckets)
• Implement data transformations and ensure efficient data processing workflows
• Collaborate with Data Architect, Data Delivery Lead, and Business Analysts to translate business requirements into technical solutions
• Propose and implement robust data models and pipeline architectures
• Orchestrate workflows using Apache Airflow / Cloud Composer
• Ensure pipelines meet high quality standards including auditability, rerun capability, modularity, reusability, and unit testing
• Contribute to CI/CD processes for deployment and pipeline automation
• Support development of data lakes, data warehouses, and dimensional models (star schema / Snowflake)