at Capgemini
ConsultanciesPosted 7 days ago
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**Data Engineering Lead** sought for Gurgaon. 9-13 years' experience needed. Lead end-to-end data strategy, architecting modern pipelines, enforcing data quality, driving performance optimization, and ensuring data governance. Manage and mentor high-performing teams. Collaborate cross-functionally to deliver impactful data solutions. Experience with Python, SQL, AWS data services, Amazon Bedrock, RAG data pipelines, alarm data processing, data quality frameworks, and network topology concepts required.
- Compensation
- Not specified
- City
- Not specified
- Country
- India
Currency: Not specified
Full Job Description
Job Description
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 Youll 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.
