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Data Engineering Lead

Your Role

Role:Data Engineering Lead
Experience:9 to 13 years
Location:Gurguram
Notiece period : Upto 60 days
 
As a Data Engineering Lead, you will own the end-to-end data engineering strategy that powers enterprise analytics and AI capabilities. You will lead the design and evolution of scalable, secure, and high-performance data platforms while ensuring data is reliable, governed, and ready for advanced use cases such as machine learning and agentic AI systems.

In this role, you will:

 

  • Architect and implement modern, scalable data pipelines supporting batch, streaming, and real-time ingestion.
  • Define and institutionalize data modeling best practices for analytical, AI, and retrieval-ready datasets.
  • Build and enforce robust data quality frameworks ensuring high trust in data across systems.
  • Drive performance optimization initiatives across ingestion, transformation, and storage layers.
  • Establish strong data governance, access control, classification, and compliance mechanisms.
  • Lead technical decision-making for large-scale data platform architecture.
  • Mentor and grow a high-performing data engineering team, fostering engineering excellence and ownership.
  • Collaborate cross-functionally with ML, RAG, MLOps, Security, and Product teams to deliver impactful data solutions.
  • Continuously evaluate and adopt new technologies to improve data platform capabilities and efficiency.

Your Profile

  • Strong hands-on experience with Python, SQL, and ETL/ELT pipeline development.
  • Experience with AWS data services: S3, Glue, Glue Data Catalog, Athena, Lambda, Step Functions, CloudWatch, IAM, KMS.
  • Working knowledge of Amazon Bedrock Knowledge Bases, Agents, Guardrails, and model inference APIs. Bedrock Guardrails can be associated with agents to validate inputs and outputs for safer GenAI applications.
  • Experience with RAG data pipelines, including document ingestion, chunking, metadata tagging, embedding generation, vector indexing, and retrieval validation.
  • Experience with alarm/event data processing, network telemetry, logs, ticket data, and topology/inventory datasets.
  • Ability to parse semi-structured data from CSV, JSON, logs, SNMP trap payloads, and alarm text.
  • Understanding of network topology concepts: device, interface, link, LAG, site, region, upstream/downstream, service dependency.
  • Experience with data quality frameworks, schema validation, deduplication, and anomaly detection.
  • Familiarity with OpenSearch, DynamoDB, Redshift, PostgreSQL, or vector databases.
  • Good understanding of security, access control, encryption, and audit logging in AWS.

What You’ll Love About Working Here

 

  • Opportunity to lead and shape next-generation data platforms powering AI and analytics at scale.
  • Work on cutting-edge technologies including AI-ready data systems, RAG pipelines, and intelligent automation.
  • Collaborative environment with highly skilled teams across data, AI, and product engineering.
  • Strong focus on innovation, engineering excellence, and continuous learning.
  • Flexible work culture that supports work-life balance and professional growth.
  • Visibility and impact — your work directly influences critical business decisions and AI capabilities.

About Us

We are a forward-thinking organization focused on building intelligent, data-driven platforms that enable scalable analytics and advanced AI capabilities. Our mission is to unlock the full potential of enterprise data by combining engineering excellence, strong governance practices, and cutting-edge AI technologies. We foster a culture of innovation, collaboration, and continuous improvement, empowering teams to solve complex challenges and deliver meaningful impact.
Ref. code:  467083
Posted on:  19 May 2026
Experience Level:  Experienced Professionals
Contract Type:  Permanent
Location: 

Gurgaon, IN

Brand:  Capgemini Engineering
Professional Community:  Manufacturing & Operations Engineering

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