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Chennai · On-site · 3-6 Yrs · 3 days ago
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
Engineer serves as a technical resource to team members, provides guidance on best practices, and contributes to the continuous improvement of data platforms and engineering processes. Primary Responsibilities:
Responsibilities
- Design, develop, and maintain scalable data ingestion, transformation, and integration pipelines
- Build and optimize ETL/ELT workflows to process structured and unstructured data from multiple sources
- Analyze business and customer requirements and translate them into technical data solutions
- Identify and resolve non-standard data challenges and moderately complex engineering problems
- Develop and maintain data models, data quality frameworks, and validation processes
- Collaborate with data analysts, data scientists, product teams, and business stakeholders to deliver trusted data assets
- Monitor and optimize pipeline performance, reliability, scalability, and cost efficiency
- Support cloud-based data platforms and data warehouse/lakehouse environments
- Implement data governance, security, lineage, and compliance standards across data assets
- Create technical documentation, design specifications, and operational procedures
- Participate in code reviews and promote engineering best practices for development, testing, and deployment
- Troubleshoot production issues, perform root-cause analysis, and implement sustainable solutions
- Contribute to automation, CI/CD processes, and continuous improvement initiatives across the data ecosystem
Qualifications
- Engineer serves as a technical resource to team members, provides guidance on best practices, and contributes to the continuous improvement of data platforms and engineering processes.
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Engineering, or a related field
- 3+ years of experience in data engineering, software engineering, or big data development
- Solid proficiency in SQL and Python for data processing and engineering
- Knowledge of cloud-based data platforms such as Azure, AWS, or Google Cloud
- Understanding of data modeling, data quality, and data governance principles
- Proven solid analytical and problem-solving skills
- Proven excellent communication and stakeholder collaboration skills
- Proven ability to work independently with minimal supervision and handle multiple priorities
- Familiarity with workflow orchestration tools such as Airflow, Azure Data Factory, or Cloud Composer
Nice to have
- Cloud platform certifications in Azure, AWS, or GCP
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Job application FAQ
Last updated 17 September 2026
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