Description

Design, build, and maintain scalable data pipelines and modernize data architecture on Google Cloud Platform.

This role is hybrid.

Responsibilities

• Design and implement ETL/ELT pipelines using Dataflow, Cloud Storage, and Pub/Sub to ingest and transform structured and semi-structured data.
• Architect and optimize BigQuery data warehouses, including query performance tuning and cloud storage cost management.
• Build orchestration workflows with Cloud Composer (Airflow) and implement CI/CD practices using Jenkins or GitHub Actions.
• Establish data quality, validation, and monitoring frameworks using Cloud Logging and Cloud Monitoring.
• Collaborate with architects and analysts to define data models (Star/Snowflake schemas, SCD) and document pipeline designs.

Required Skills

• 9+ years of experience in data engineering with strong expertise in ETL/ELT pipeline design.
• Proficiency in Python for data processing and scripting.
• Advanced SQL skills with deep knowledge of query optimization, partitioning, and clustering.
• Hands-on experience with GCP services: BigQuery, Cloud Storage, Dataflow/Apache Beam, Pub/Sub, and Cloud Composer.
• Strong understanding of data warehousing concepts, including Star/Snowflake schemas and Slowly Changing Dimensions (SCD).
• Experience with CI/CD tools such as Git, Jenkins, or GitHub Actions.
• Familiarity with IAM and security best practices in cloud environments.

Preferred Skills

• Experience with Cloud Functions or Cloud Run for serverless data tasks.

Key Skills

Education

Any Gradute