Data Engineer - Gen AI data pipeline - Consultant (I&T - Deloitte Engineering)

Deloitte

5 - 10 years

Bengaluru, Kolkata

Posted: 08/07/2025

Job Description

Position Summary

Job Role: Data Engineer Gen AI Data Pipeline- Consultant



Are you looking to work at a place that builds robust, high-quality software solutions?  Deloitte Consulting is the answer.    As an Analyst/Consultant/Engineer at Deloitte Consulting, you will be

responsible for quality assurance on large-scale complex software solutions at enterprise level. These applications are often high-volume mission critical systems that would provide you an exposure with end-to-end functional and domain knowledge. You will work with business, functional and technical teams on the project located across shores. You will be responsible to independently lead a team, mentor team members, and drive all test deliverables across project life cycle. You will be involved in end-to-end delivery of the project from testing strategy, estimations, planning, execution and reporting. 

Work youll do

A Cloud Data Engineer will be responsible for following activities: 

 

      Participate in application architecture and design discussions. Work with team leads in defining solution Design for development. 

      Analyze business/functional requirements and develop data processing pipelines for them. 

      Perform unit testing and participate in integration in collaboration with other team members. 

      Perform peer code reviews and ensure its alignment with pre-defined architectural standards, guidelines, best practices, and meet quality standards. 

      Work on defects\bugs and help other team members. 

      Understand and comply with the established agile development methodology. Participate in various Agile ceremonies like scrum meetings, sprint plannings etc. 

      Proactively identify opportunities for code/process/design improvements. 

      Participate in customer support activities for existing clients using Converge Healths existing platform\products. 

The Team

Deloitte Consulting LLPs Technology Consulting practice is dedicated to helping our clients build tomorrow by solving todays complex business problems involving strategy, procurement, design, delivery, and assurance of technology solutions. Our service areas include analytics and information management, delivery, cyber risk services, and technical strategy and architecture, as well as the spectrum of digital strategy, design, and development services offered by Deloitte Digital. Learn more about our Technology Consulting practice on www.deloitte.com. 

Qualifications and Experience

Required:

Education: 

 

B.E./B.Tech/M.C.A./M.Sc. 

 

Data Engineering Principles: 

  • Proficient in data warehousing concepts. 
  • Experienced with ETL (Extract, Transform, Load) processes. 
  • Skilled in SQL and handling data in JSON and other semi-structured formats. 
  • Hands-on experience with Python for data processing tasks. Big Data and Cloud Platforms: 
  • Experience with Big Data technologies on cloud platforms such as AWS or Cloudera.

  • AWS Cloud Platform:Working experience on the AWS cloud platform. 
  • AWS Data Pipeline: 
  • Knowledgeable in building data pipelines on AWS using services like Lambda, S3, Athena, Kinesis, etc.   
  • Performance Tuning:  
  • Proficient in performance tuning on various RDBMS (Relational Database Management Systems) such as Oracle, SQL Server, Redshift, Impala, etc. 
  • Data Modeling Concepts: 
  • Good understanding of dimensional, relational, or hybrid data modeling.     
  • Continuous Integration Tools:   
  • Experience with CI tools such as Jenkins.  
  • Proficient with GIT version control systems. 
  •  Familiar with issue tracking tools like JIRA.    
  • Agile Development:   
  • Familiar with Agile development methodologies.  
  • Generative AI Experience: 
  • Retrieval-Augmented Generation (RAG): 
  • Must have Implemented RAG techniques to enhance data retrieval and improve the relevance of generated content.
  • Integrated RAG models with existing data pipelines to optimize information retrieval processes. 
  • Vector Databases: Utilizing vector databases for efficient storage and retrieval of high-dimensional data. 
  • Knowledge on vector search algorithms to enhance the performance of AI-driven applications. 
  • Large Language Models (LLMs): 
  • Experience with deploying and fine-tuning large language models for various NLP tasks.  
  • Integrated LLMs into data processing workflows to automate and enhance data analysis. 
  • LangChain: 
  • Knowledge on LangChains for building and managing complex data workflows.
  • Experience in scalable data pipelines using LangChain to streamline data processing and integration tasks. 
  • Efficiency Improvements :Should have implementation experience to reduce data processing times by optimizing ETL workflows and leveraging cloud-native solutions. 

Data Engineering Principles: 

  • Proficient in data warehousing concepts. 
  • Experienced with ETL (Extract, Transform, Load) processes. 
  • Skilled in SQL and handling data in JSON and other semi-structured formats. 
  • Hands-on experience with Python for data processing tasks. Big Data and Cloud Platforms: 
  • Experience with Big Data technologies on cloud platforms such as AWS or Cloudera.
  • AWS Cloud Platform:Working experience on the AWS cloud platform. 
  • AWS Data Pipeline: 
  • Knowledgeable in building data pipelines on AWS using services like Lambda, S3, Athena, Kinesis, etc.   
  • Performance Tuning:  
  • Proficient in performance tuning on various RDBMS (Relational Database Management Systems) such as Oracle, SQL Server, Redshift, Impala, etc. 
  • Data Modeling Concepts: 
  • Good understanding of dimensional, relational, or hybrid data modeling.     
  • Continuous Integration Tools:   
  • Experience with CI tools such as Jenkins.  
  • Proficient with GIT version control systems. 
  •  Familiar with issue tracking tools like JIRA.    
  • Agile Development:   
  • Familiar with Agile development methodologies.  
  • Generative AI Experience: 
  • Retrieval-Augmented Generation (RAG): 
  • Must have Implemented RAG techniques to enhance data retrieval and improve the relevance of generated content.

    About Company

    Deloitte is a global professional services firm that provides a wide range of services, including audit and assurance, consulting, tax, risk management, and financial advisory. With a presence in over 150 countries and a network of member firms, Deloitte serves clients across various industries, helping them solve complex business challenges, improve operations, and innovate. Known for its expertise in management consulting, technology solutions, and strategy, Deloitte is one of the Big Four accounting firms and is recognized for its commitment to quality, integrity, and making an impact in the marketplace.

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