Senior Manager Data Engineering

Overview

Lead a team building trusted enterprise data products and production-ready AI capabilities, owning engineering delivery across data pipelines, semantic models, enterprise context layers, and AI agent integrations.

What you'll do

• Recruit, coach, and develop data and AI engineers, establishing clear ownership, development plans, and accountability for engineering quality and delivery.
• Lead the development of scalable ingestion and transformation pipelines, curated datasets, and reusable data products across business domains.
• Guide semantic modeling, metadata pipelines, knowledge graph integrations, and enterprise context services that give AI applications consistent business definitions and relationships.
• Establish service expectations, monitoring, incident response, support handovers, and cost controls for data pipelines and AI services.
• Own roadmaps, capacity planning, technical dependencies, and delivery across multiple initiatives.
• Track data reliability, delivery performance, AI answer quality, adoption, time saved, and operating costs to guide investment decisions.
• Partner with business and architecture leaders to prioritize high-value use cases and establish engineering standards.

What you'll need

• Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• Typically 10+ years of experience in data engineering, software engineering, or related disciplines, including 3+ years leading data engineering teams.
• Proven experience delivering and supporting enterprise data platforms and business-critical data pipelines.
• Strong technical foundation in SQL, Python, dimensional modeling, distributed processing, and cloud architecture.
• Experience with Google Cloud services such as BigQuery, Cloud Storage, Composer/Airflow, and Dataform, or comparable cloud technologies.
• Practical experience delivering AI-enabled applications, including LLM integration, retrieval-augmented generation, tool calling, and evaluation.
• Understanding of semantic models, metadata management, knowledge graphs, and their role in grounding AI responses.
• Experience implementing automated testing, CI/CD, data quality monitoring, and production support practices.
• Demonstrated ability to manage competing priorities, lead cross-functional delivery, and communicate technical decisions clearly.

Details

• Location: Bangalore, India.