The Team

Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data. Our global network provides strategic guidance and implementation services to help companies manage data from disparate sources and convert it into accurate, actionable information that can support fact-driven decision-making and generate an insight-driven advantage. Our practice addresses the continuum of opportunities in business intelligence & visualization, data management, performance management and next-generation analytics and technologies, including big data, cloud, cognitive and machine learning.

Your work profile

The GCP data engineer is responsible for managing client relationships and overseeing the successful delivery of programs or accounts. This role serves as the primary point of contact between the organization and its clients, ensuring alignment of goals, timelines, budgets, and expected outcomes while driving client satisfaction and business growth.

Key Skills & Competencies

Experience
5–8 years of overall IT experience




Minimum 3+ years in GCP Data Engineering projects
Experience working in consulting or large-scale enterprise environments

Technical Expertise
Solid hands-on experience with Google Cloud Platform (GCP)
Expertise in:
BigQuery
Dataflow
Dataproc
Pub/Sub
Cloud Composer (Airflow)
Solid programming skills:
Python
SQL
Experience with:
Spark, Hadoop, or distributed data processing frameworks
ETL/ELT frameworks and data warehousing concepts
Batch and real-time data processing
Familiarity with:
Git and version control systems
CI/CD pipelines
Agile development methodologies
Understanding of:
Data governance
Data security best practices

Architecture & Engineering
Designing and building scalable ETL/ELT pipelines on GCP
Developing cloud-native data architectures using GCP services
Implementing data models, quality checks, and governance framework

📌 Senior Consultant Gcp Data Engineer Ahmedabad Engineering Data Modernization
🏢 Deloitte
📍 Ahmedabad