Data Engineer, VP

Overview

As a Data Engineer at vice president level, design, build and operate scalable data and knowledge engineering capabilities that power strategic AI platforms, including Conversational AI, Knowledge Studio, AI Knowledge Bases and other intelligent services.

What you'll do

• Build and maintain automated data, content and knowledge ingestion pipelines from enterprise repositories and digital channels.
• Develop solutions to transform documents and unstructured content into AI-ready formats, including metadata enrichment, content segmentation and knowledge preparation.
• Design and implement retrieval, indexing and vectorisation pipelines to support Generative AI and Retrieval-Augmented Generation (RAG) solutions.
• Integrate knowledge and AI services with AWS platforms including Amazon Bedrock and SageMaker Unified Studio.
• Build advanced automation capabilities by removing manual processing activities and improving operational efficiency.
• Develop APIs, reusable services and event-driven solutions to support Knowledge Studio, Conversational AI and AI-powered customer journeys.
• Implement controls for data quality, knowledge quality, governance, PII detection and regulatory compliance.
• Deliver monitoring, observability and operational controls for data and AI platforms.
• Support experimentation, innovation and implementation of emerging AI technologies and AI engineering practices.
• Contribute to architecture, engineering standards and best practices across data and AI platforms.
• Develop solutions for batch, streaming and event-driven data ingestion and transformations in line with strategic technology direction.
• Work collaboratively across engineering, architecture, product and business teams to deliver enterprise-scale AI solutions.

What you'll need

• 12+ years in the mentioned skillsets.
• Strong experience in Python and SQL development.
• Experience designing and building ETL/ELT pipelines and data processing frameworks.
• Hands-on experience with AWS cloud services and cloud-native solution development.
• Experience working with Amazon Bedrock.
• Experience working with SageMaker Unified Studio.
• Experience working with Amazon S3.
• Experience working with AWS Lambda.
• Experience working with AWS Glue.
• Experience working with DynamoDB.
• Experience working with ECS/Fargate.
• Experience working with Step Functions.
• Experience working with EventBridge.
• Experience working with OpenSearch.
• Experience building REST APIs and microservices.
• Strong understanding of data engineering fundamentals, data modelling and data architecture principles.
• Experience working with structured and unstructured data.
• Experience with modern software engineering practices including Git, GitLab, CI/CD and automated testing.
• Knowledge of data quality frameworks, monitoring and observability.
• Experience working in a governed and regulated environment.
• Strong communication skills with the ability to proactively engage and manage a wide range of stakeholders.

Nice to have

• Experience with Generative AI technologies and Large Language Models (LLMs).
• Understanding of Retrieval-Augmented Generation (RAG) architectures and knowledge retrieval concepts.
• Experience working with embeddings, semantic search and vector databases.
• Knowledge of document transformation, content processing and knowledge engineering practices.
• Experience building knowledge management, content ingestion or AI-driven information platforms.
• Building and maintaining automated data, content and knowledge ingestion pipelines from enterprise repositories and digital channels.
• Developing solutions to transform documents and unstructured content into AI-ready formats including metadata enrichment, content segmentation and knowledge preparation.
• Designing and implementing retrieval, indexing and vectorisation pipelines to support Generative AI and Retrieval-Augmented Generation (RAG) solutions.
• Integrating knowledge and AI services with AWS platforms including Amazon Bedrock and SageMaker Unified Studio.

Details

• Location: Gurugram.
• Hours: 45.