Lead - AI Data Intelligence (ETL,Azure, SQL, Python, Spark, Data Lakehouse) 7 - 11 years exp from SaaS companies
Core
Lead cross-functional engineering pods to design, build, and deploy production Text-to-SQL and Natural Language Query (NLQ) platforms that enable non-technical business teams to query enterprise data.
Role type
Senior IC Lead - AI Data Intelligence (ETL, Azure, SQL, Python, Spark, Data Lakehouse)
Builds
Production-grade Text-to-SQL and Natural Language Query (NLQ) platforms connecting operational systems to cloud lakehouses
Domain
SaaS / Beauty and Wellness / AI Data Intelligence
Deliverable
production ML models
Required skills
Enterprise-scale distributed software and cloud systems, .NET/C# REST APIs, SQL Server, Amazon Redshift, Databricks (Delta Lake, Unity Catalog), Python, FastAPI, LLM orchestration, agentic architectures, Text-to-SQL, NLQ systems, semantic layer architecture, business ontology modelling, conversational UI workflows, AI-assisted development tools
Preferred skills
Conversational analytics tools (Databricks Genie), modern frontend frameworks (React, Flutter, Next.js), AI guardrails and evaluation suites
Technologies
AWS, Azure, .NET, C#, Microsoft SQL Server, React, Flutter, Python, FastAPI, Amazon Redshift, Databricks, Delta Lake, Unity Catalog, Claude Code, Cursor, Copilot
Responsibilities
Lead cross-functional engineering pods to design, build, and deploy production Text-to-SQL and NLQ platforms; Act as a technical advisor partnering with client stakeholders to diagnose bottlenecks and scope use cases; Architect governed semantic layers, business ontologies, and metric views; Build robust microservices and event-driven data pipelines; Partner with product managers and frontend engineers to build conversational data experiences; Put in place enterprise AI guardrails and observability frameworks; Champion modern AI-assisted engineering practices
Seniority
Senior, hands-on IC with leadership
