We are seeking a skilled and experienced Data Engineer with strong expertise in Google Cloud Platform (GCP) to design, build, and optimize scalable data pipelines and modern data platforms. The ideal candidate should have hands-on experience in BigQuery, PySpark, and Medallion Architecture, along with strong proficiency in Python and advanced SQL.

You will play a key role in developing robust data solutions, enabling data-driven decision-making, and ensuring high data quality and governance across the platform.

Key Responsibilities :

- Design, develop, and maintain scalable data pipelines using PySpark and Cloud Dataflow

- Build and manage data platforms based on Medallion Architecture (Bronze, Silver, Gold layers)

- Work extensively with BigQuery for data warehousing, optimization, and performance tuning

- Orchestrate workflows using Cloud Composer (Apache Airflow)

- Ingest, process, and store large datasets using Google Cloud Storage (GCS)

- Collaborate with cross-functional teams to understand business requirements and translate them into data solutions

- Ensure data quality, integrity, and governance across the data lifecycle

- Implement CI/CD pipelines and manage version control using Git

- Manage access control and security using GCP IAM

- Monitor and optimize data pipelines for performance and cost efficiency

Primary Skills :

- Google Cloud Platform (GCP)

- BigQuery

- Data Platform (Medallion Architecture)

- PySpark

- Python

- Advanced SQL

- Cloud Dataflow

- Cloud Composer (Airflow)

- Google Cloud Storage (GCS)

- Version Control & CI/CD

- Git

- GCP IAM

Secondary Skills (Good to Have) :

- Experience with data governance and data quality frameworks

- Knowledge of data modeling and ETL/ELT best practices

- Exposure to monitoring tools and logging frameworks in GCP

- Understanding of DevOps practices in cloud environments