Data Engineer

TymblHub; Gurugram District; On-site; INR 1,500,000 - 3,000,000; Full time

Benefits offered by this job

Learning & development opportunities

Collaborative team environment

Cutting-edge AI/GenAI projects

Job summary

Capgemini is hiring a Data Engineer to design, build, and maintain enterprise data platforms supporting AI-driven products and analytics initiatives in Gurgaon, India.

You will work with Python, SQL, Spark, Kafka, and AWS services to develop data pipelines, digital twin platforms, and AI-ready data architectures, collaborating with data scientists and business stakeholders across the organization.

Qualifications

• Strong Python and SQL programming skills.
• Experience with Spark, Spark Streaming and Kafka.
• Knowledge of data modeling, ETL/ELT and data architecture.
• Experience building data lakes and managing AWS services (S3, Glue, Lambda).
• Familiar with ML/DL, predictive analytics and generative AI tech.
• Exposure to LLMs, RAG, AI agents and knowledge graphs.

Responsibilities

• Design and implement data source connectors for telemetry and enterprise apps.
• Build ingestion, validation, replay, and data contract frameworks for large-scale data onboarding.
• Develop topology mapping to transform raw telemetry into incident-aware datasets.
• Design, develop, and maintain digital twin and topology graph platforms.
• Build and manage Knowledge Graphs, ontologies, and semantic data models.
• Develop reusable feature engineering frameworks and feature stores for AI/ML.
• Enable data foundations for RAG, vector databases, and AI agent frameworks.
• Optimize pipelines for model training, deployment, monitoring and lifecycle.
• Implement metadata management, lineage tracking, observability, governance.
• Collaborate with data scientists, AI engineers and stakeholders to deliver scalable AI analytics.

Skills

Python

SQL

Data modeling

ETL/ELT

Data architecture

Apache Spark

Spark Streaming

Kafka

AWS

SageMaker

ML/DL

Generative AI

LLMs / Retrieval-Augmented Generation

AI Agents

Knowledge Graphs

Digital Twin

Graph/Vector databases

APIs

Data governance

Tools

AWS

SageMaker

Spark

Kafka

Data Lakes

Graph Databases

Vector Databases

Job description

# Data EngineerCapgeminiPosted on October 15, 2026---Job LocationGurgaon / Gurugram, IndiaVacancy1DesignationData EngineerJob TypeONSITE---## Job Description## Job SummaryAs a Data Engineer at Capgemini, you will design, build, and maintain enterprise data platforms supporting AI-driven products and analytics initiatives. You will work with **Python**, **SQL**, **Apache Spark**, **Kafka**, and **AWS** services to develop robust data pipelines, digital twin platforms, knowledge graphs, and AI-ready data architectures.## About the RoleChoosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world.As a Data Engineer, you will design, build, and maintain enterprise data platforms that support AI-driven products and analytics initiatives. You will work closely with Data Scientists, Architects, AI Engineers, and business stakeholders to develop robust data pipelines, digital twin platforms, knowledge graphs, and AI-ready data architectures.## Key Responsibilities* Design and implement data source connectors for telemetry, topology, intent, ITSM, knowledge repositories, and enterprise applications.* Build ingestion, validation, replay, and data contract frameworks for large-scale data onboarding.* Develop ingestion and topology mapping capabilities to transform raw telemetry into incident-aware datasets.* Design, develop, and maintain Network Digital Twin and topology graph platforms.* Build and manage Knowledge Graphs, ontology frameworks, entity relationships, and semantic data models.* Develop reusable Feature Engineering Frameworks and Feature Store capabilities for AI/ML applications.* Enable data foundations for RAG, GraphRAG, Vector Databases, and AI Agent frameworks.* Develop and optimize data pipelines for model training, deployment, monitoring, and lifecycle management.* Implement metadata management, lineage tracking, observability, security, auditing, and governance frameworks.* Support integrations with AI reasoning engines, recommendation systems, and agent orchestration platforms.* Collaborate with cross-functional teams to deliver scalable, enterprise-grade AI and analytics solutions.## Requirements* Strong programming expertise in **Python** and **SQL**.* Experience with **JavaScript, React, or Angular**.* Strong knowledge of **Data Modeling, ETL/ELT, and Data Architecture** principles.* Hands-on experience with **Apache Spark**, **Spark Streaming**, and **Kafka**.* Experience building and managing **Data Lakes**.* Strong experience with **AWS** services including: S3, Glue, Lambda, SageMaker.* Knowledge of **Machine Learning**, **Deep Learning**, **Predictive Analytics**, and **Statistical Modeling**.* Experience with **Generative AI** technologies including: Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), AI Agents, Agentic AI Frameworks.* Expertise in: Relational Databases, Graph Databases, Vector Databases.* Experience building APIs, Data Pipelines, and Batch/Real-Time Data Processing frameworks.* Strong understanding of: Data Quality, Metadata Management, Data Lineage, Data Governance.* AWS Glue and Azure Data Factory experience.* SageMaker Pipelines experience.* Experience with Digital Twin platforms and architectures.* Knowledge of GraphRAG and advanced RAG solutions.* MLOps and LLMOps implementation experience.* DataOps practices and automation frameworks.* Experience with Enterprise Knowledge Management Platforms.* Strong analytical, debugging, and problem-solving skills.## Benefits* Opportunity to work on cutting-edge AI, GenAI, Knowledge Graph, and Digital Twin technologies.* Exposure to enterprise-scale AI and analytics transformation initiatives.* Collaborative environment with Data Scientists, AI Engineers, Architects, and domain experts.* Continuous learning opportunities across Data Engineering, GenAI, MLOps, and Cloud technologies.* Ability to build scalable AI data foundations that drive measurable business impact and innovation.* Innovation-driven culture focused on engineering excellence and technical growth.