Lead - AI Data Intelligence (ETL,Azure, SQL, Python, Spark, Data Lakehouse) 7 - 11 years exp from SaaS companies
About this role
Data professionals who thrive on bridging the gap between non-technical business users and complex cloud data architectures will find a compelling challenge in this role. Zenoti is expanding its enterprise software capabilities for the global wellness industry by developing production-grade Text-to-SQL and Natural Language Query platforms that link operational databases to cloud lakehouses.
Operating from Hyderabad, the chosen lead will design governed semantic models, guide cross-functional engineering pods, and establish rigorous AI guardrails and observability frameworks for large-scale data products. This position suits an experienced technical leader who combines deep expertise in distributed .NET and Python environments with hands-on delivery of conversational analytics and LLM-driven applications.
What you will do
- Lead cross-functional engineering pods to design, build, and deploy production Text-to-SQL and Natural Language Query platforms for non-technical business teams.
- Partner directly with client stakeholders and business leaders to diagnose operational bottlenecks and scope high-impact use cases.
- Architect governed semantic layers, business ontologies, metric views, and parameter mappings grounded in verified business logic.
- Build robust microservices, REST APIs, and event-driven data pipelines connecting backend systems with modern Python, FastAPI, Databricks, and Amazon Redshift platforms.
- Collaborate with product managers, UI/UX designers, and frontend engineers to deliver responsive conversational data experiences.
- Implement enterprise AI guardrails, evaluation suites, and observability frameworks to ensure safety, data privacy, and reliability in production.
- Champion modern AI-assisted engineering practices and create reusable engineering assets to accelerate team velocity.
What you need
- Over 8 years of experience designing, building, and operating enterprise-scale distributed software and cloud systems with mastery of OOP and modern .NET/C# REST APIs.
- Deep expertise in SQL Server relational schema design, complex joins, views, and aggregations, complemented by hands-on experience on Amazon Redshift and Databricks.
- At least 2 years of dedicated, hands-on production experience navigating the AI development lifecycle, including LLM orchestration and agentic architectures.
- Advanced proficiency in Python and FastAPI for developing asynchronous microservices, data validation schemas, and enterprise integration gateways.
- Practical experience building Text-to-SQL and Natural Language Query systems with semantic layer architecture and business ontology modelling.
- Proven solutions engineering acumen in client-facing environments to translate business goals into technical architectures.
- Strong technical leadership experience mentoring senior engineers and guiding delivery pods.
- A bachelor’s or master’s degree in computer science, Software Engineering, Information Systems, or equivalent practical industry experience.
Nice to have
- Hands-on experience building scalable data pipelines on Amazon Redshift and Databricks (Delta Lake, Unity Catalog)
- Experience designing conversational UI workflows with exposure to benchmark products like Databricks Genie or comparable conversational analytics tools
- Familiarity with modern frontend frameworks such as React, Flutter, or Next.js
- Hands-on familiarity with modern AI-assisted development tools like Cursor, Claude Code, and Copilot
Benefits
- Competitive compensation package
- Comprehensive medical coverage for you and your family
- Holistic wellness benefits including yoga, meditation and stress management
- Regular team and social events and community service opportunities
Skills and tech stack
Questions candidates ask
What kind of systems will I be building in this role?
You will engineer production-grade Text-to-SQL and Natural Language Query platforms that connect operational systems to cloud lakehouses across Amazon Redshift and Databricks via high-performance Python and FastAPI microservices. This includes architecting governed semantic layers and building conversational data experiences for business users.
What are the core technical requirements for applicants?
Candidates need 7 to 11 years of total experience from SaaS companies, featuring 8+ years in distributed software and cloud systems with .NET/C# REST APIs, plus 2+ years of hands-on production experience in the AI development lifecycle including LLM orchestration and agentic architectures.
What benefits are provided with this position?
Zenoti offers a competitive compensation package, comprehensive medical coverage for you and your family, holistic wellness benefits including yoga, meditation, and stress management, as well as regular team and social events.