Seeking an experienced GCP Data Engineering Manager with 8 to 15 years in the field to spearhead the development and enhancement of cloud-based data platforms. This role demands a blend of deep GCP data service expertise and practical performance engineering skills for large-scale Spark and Dataproc environments. The position is based in Ahmedabad, IN, focusing on Data Modernization & Migration initiatives.

Key duties include designing and implementing data solutions leveraging GCP services such as Cloud Run, Cloud Functions with Python, Cloud SQL PostgreSQL, Pub/Sub, GCS, and BigQuery. You will build and manage orchestration workflows using Cloud Composer/Managed Airflow, focusing on optimization, cost governance, and FinOps. The role also involves supporting Databricks, integrating REST APIs, and providing crucial technical leadership, architectural guidance, and delivery oversight to engineering teams.

Furthermore, this position entails executing workload test waves, enhancing Python execution templates, and troubleshooting Spark, YARN, and Dataproc failures through Spark UI and platform diagnostics. You'll analyze workload profiles to capture cost-performance benchmarks, define machine type strategies, and recommend VM sizing and schema design for optimal performance of Big Data workloads.

A minimum of 8 to 15 years of experience in Data Engineering, with substantial hands-on experience in GCP, is essential. Proficiency in Python, Spark, Dataproc, GCS, BigQuery, and Cloud Data Architecture is required. Familiarity with Cloud Run, Cloud Functions, Cloud SQL PostgreSQL, and Pub/Sub is necessary. Experience in Cloud Composer/Airflow administration, optimization, and FinOps is crucial, as is skill in Spark UI debugging, YARN diagnostics, and workload benchmarking.

Exceptional stakeholder management, team leadership, and solution design capabilities are vital. A Bachelor of Engineering (B.E.) or Bachelor of Technology (B.Tech.) degree is a prerequisite. This is an onsite position located in Ahmedabad, India.