Description

Build and maintain scalable data pipelines on Google Cloud Platform to support AI/ML models and enterprise analytics.

This role is on-site.

Responsibilities

• Design and build scalable ETL/ELT pipelines using Apache Airflow, Apache Spark, and GCP Dataflow.
• Develop and maintain BigQuery data models, schemas, and performance-optimized SQL queries.
• Build pipelines feeding AI/ML feature stores and collaborate with AI Developers on low-latency data access.
• Manage and optimize Cloud Composer DAGs, implement data quality monitoring, and track lineage.
• Participate in data platform architecture decisions and documentation.

Required Skills

• 5+ years of data engineering experience.
• Hands-on experience with Apache Airflow for pipeline orchestration.
• Proficiency in Apache Spark for large-scale data processing.
• Strong SQL skills including complex query optimization and BigQuery-specific capabilities.
• Experience with GCP data services: BigQuery, Cloud Storage, Pub/Sub, Dataflow.
• Solid understanding of ETL/ELT patterns and data warehousing principles.
• Bachelor's degree.

Preferred Skills

• GCP Professional Data Engineer certification.
• Experience supporting ML/AI data infrastructure (feature engineering, training datasets).
• Familiarity with real-time streaming (Kafka, Dataflow/Flink).

Key Skills

Education

Bachelor's degree