AI Data & Knowledge Engineer – Senior Manager

Overview

Design and deliver scalable data pipelines and knowledge systems that support enterprise AI use cases, combining core data engineering with AI-specific capabilities such as RAG, GraphRAG and knowledge graph enablement.

What you'll do

• Design, build and maintain scalable batch and streaming data pipelines to ingest, transform and serve data for AI and analytics use cases.
• Own end-to-end ETL/ELT workflows for domain data, including ingestion from enterprise systems, cleansing, transformation, enrichment and publishing.
• Build AI-ready datasets and retrieval pipelines that support RAG, GraphRAG, semantic search and knowledge-driven applications.
• Develop and manage knowledge graphs, ontologies, metadata layers and data contracts for assigned domains.
• Implement and support vector indexing, chunking, hybrid retrieval and backend data preparation workflows for AI services.
• Own integration patterns between source systems, data platforms and AI application layers, including MCP server integrations where relevant.
• Monitor pipeline health, data quality, latency, throughput and reliability; troubleshoot production issues and optimize performance.
• Mentor junior engineers and contribute to best practices for data engineering, data governance and AI data enablement.

What you'll need

• Bachelor's or Master's degree in Computer Science, Data Engineering, Information Systems or a related field.
• 5–10 years of experience in data engineering, platform engineering or backend data systems.
• Strong hands-on experience with Python and SQL.
• Experience building production ETL/ELT pipelines and scalable data integration workflows.
• Experience with big data and distributed processing frameworks such as Spark, Databricks, Hadoop ecosystem components or equivalent platforms.
• Familiarity with workflow orchestration tools such as Airflow or similar.
• Experience working with cloud data platforms, warehouses or lakehouses such as Snowflake, Databricks, BigQuery, Redshift or equivalent.
• Understanding of data contracts, metadata management, data lineage and data governance practices.

Nice to have

• Hands-on exposure to RAG, GraphRAG, vector databases or knowledge graphs in enterprise settings.
• Experience with streaming/event-driven patterns using Kafka, Kinesis or similar tools.
• Cloud certifications in AWS and/or Azure.

Details

• Location: Hyderabad, India.
• Work schedule: On-premise.