Description

Architect and lead the strategy for enterprise-scale ETL/ELT pipelines and data governance on Google Cloud Platform.

This role is on-site.

Responsibilities

• Lead the architecture and development of ETL/ELT pipelines using Python, Apache Airflow, and dbt Core.
• Define and enforce data management standards across the full data lifecycle, including ingestion, quality, governance, and archival.
• Drive adoption of cloud-native orchestration (Cloud Composer) and storage (GCS) within the enterprise data platform.
• Mentor engineers, establish engineering best practices, and lead root-cause analysis for pipeline performance optimization.
• Implement CI/CD automation and observability tooling to ensure reliable data delivery.

Required Skills

• 8+ years of experience in data engineering with demonstrated leadership responsibility.
• Deep expertise in Python, Apache Airflow, and dbt Core for enterprise-scale data pipelines.
• Proven experience designing large-scale data warehouses and data platforms on Google Cloud Platform (GCP).
• Strong proficiency in SQL and data warehousing concepts.
• Experience defining data governance, cataloging, and lineage strategies.
• Ability to partner with product and business stakeholders to align data strategy with roadmap planning.

Preferred Skills

• Experience with event streaming platforms like Kafka.
• Familiarity with data lifecycle management tools for retention and archival.

Key Skills

Education

Any Graduate