Description

Design and build scalable cloud-native data platforms on Google Cloud Platform, owning the architecture for batch, streaming, and event-driven pipelines.

This role is on-site.

Responsibilities

• Architect and develop reusable data ingestion, transformation, and orchestration frameworks using BigQuery, Dataflow, Pub/Sub, and Cloud Composer.
• Design and implement scalable data mesh architectures, creating reusable data products and semantic layers for enterprise analytics.
• Establish data governance, quality, and metadata management frameworks to ensure reliability and compliance across data assets.
• Optimize pipeline performance, cost efficiency, and scalability while mentoring data engineers on technical best practices.

Required Skills

• 8-10 years of experience in Data Engineering and Data Platform Development.
• Minimum 4 years of hands-on experience with Google Cloud Platform (GCP).
• Strong proficiency in BigQuery, Dataflow, Pub/Sub, and Cloud Composer (Airflow).
• Proven experience building large-scale batch and streaming data pipelines.
• Deep understanding of data architecture, data mesh principles, and data-as-a-product concepts.
• Experience with data governance, metadata management, and data modeling.
• Ability to lead technical design discussions and translate business requirements into scalable solutions.

Preferred Skills

• Experience supporting AI/ML data use cases and enterprise reporting requirements.
• Strong background in performance tuning and troubleshooting complex data systems.

Key Skills

Education

Any Graduate