Deloitte
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Ahmedabad · On-site · 5-8 Yrs · Aug 17
Business consulting · 10000+ Employees · New York, US
Deloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private companies. Our more than 412,000+ professionals deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger economy, a more equitable society and a sustainable world. Building on its 178-plus year history, Deloitte spans more than 150 countries and territories. Deloitte US-India Offices is part of region within the Deloitte US organization, with offices across seven cities in India — Hyderabad, Mumbai, Delhi-NCR, Bengaluru, Kolkata, Pune and Chennai.
Hiring: Engineering
What employees say
+ Very good hike and bonus. Flexible with respect to timings.
− Extended work hours is the only con.
More reviews on the company profile.
Interview experience · Technology Manager
The interview process typically includes a telephonic screening, two technical rounds, a managerial round, a CA round, and an HR discussion. The process is well-structured and evaluates technical knowledge, problem-solvi
Difficult difficulty · Bengaluru · 8,233 reports
More interview insightsJob description
Overview
Deloitte’s Technology & Transformation practice can help you uncover and unlock the value buried deep inside vast amounts of data.
Qualifications
- 5–8 years of overall IT experience
- Minimum 3 years in GCP Data Engineering projects
- Strong hands-on experience with Google Cloud Platform (GCP)
- Expertise in:
- BigQuery
- Dataflow
- Dataproc
- Pub/Sub
- Cloud Composer (Airflow)
- Strong programming skills:
- Python
- SQL
- 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
- Designing and building scalable ETL/ELT pipelines on GCP
- Developing cloud-native data architectures using GCP services
- Implementing data models, quality checks, and governance frameworks
- Optimizing SQL queries and improving pipeline performance
- Supporting on-premise to cloud data migration initiatives
- Ensuring platform scalability, monitoring, and reliability
- Collaborating with architects, analysts, and business stakeholders
- Participating in agile delivery processes and sprint execution
Education
- Delivery of scalable and optimized GCP data solutions
- Efficient and reliable data pipelines and platforms
- Strong collaboration with stakeholders and teams
- Adherence to best practices in engineering, governance, and security
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