Responsible for developing, optimizing, and maintaining business intelligence and data warehouse solutions with expertise in Google Cloud Platform (GCP). Lead the transition of legacy databases, data warehouses, and multi-cloud workloads to contemporary GCP architectures, ensuring secure, scalable, and effective data processing. Enable self-service analytics, improve data accessibility, and provide stakeholders with impactful reporting and analytical insights to support strategic business decisions.
Grade: T5:
What Your Main Responsibilities Are:
Accountabilities:
Data Pipeline Engineering
Design, develop, and maintain scalable, reliable, and high-performance data pipelines to support growing data volumes and complexity.
Build and manage APIs, data ingestion frameworks, and streaming/batch data processing solutions on Google Cloud Platform (GCP).
Cloud Data Integration
Integrate structured and unstructured data from multiple online and offline sources to create a unified view of customer, operational, and business data.
Perform data acquisition, processing,



transformation, analysis, and visualization to enable advanced analytics and personalization initiatives.
Support migration and integration of legacy databases, on-premises data platforms, and other cloud settings into GCP.
Data Quality & Governance
Drive data quality, consistency, and readiness for enterprise analytics.
Define, implement, and continuously improve data governance frameworks, standards, controls, and best practices.
Establish data validation, monitoring, lineage, and metadata management processes across data platforms.
Data Transformation & Engineering
Design and implement ETL/ELT frameworks to cleanse, enrich, and transform data for analytical and operational consumption.
Develop optimized data models and storage structures to support reporting, self-service analytics, machine learning, and business intelligence workloads.
Data Enablement & Analytics
Ensure ente

📌 Data Engineer Senior Ii Mumbai
🏢 Fedex AMEA
📍 Mumbai