Lead- AI Data Intelligence (ETL,Azure,SQL,Python,Spark,Data Lakehouse)

Lead - AI Data Intelligence

About the Role

Our enterprise products run across AWS and Azure, built on a mission-critical transactional backbone of .NET, C#, Microsoft SQL Server, and extensive RESTful APIs, with modern interfaces delivered via React and Flutter. As we advance our data intelligence capabilities, we are engineering production-grade Text-to-SQL and Natural Language Query (NLQ) platforms that connect operational systems to cloud lakehouses across Amazon Redshift and Databricks (Delta Lake and Unity Catalog) via high-performance Python and FastAPI microservices. In this role, you will act as a technical leader and strategic advisor-partnering directly with business stakeholders to scope high-value analytical workflows, designing governed semantic models and metric ontologies, and guiding engineering pods to build and deploy reliable, conversational data products capable of handling terabytes of data and millions of records with 24x7 enterprise availability.

What will I be doing

• 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.
• Act as a technical advisor, partnering directly with client stakeholders and business leaders to diagnose operational bottlenecks, scope high-impact use cases, and deliver working solutions.
• Architect governed semantic layers, business ontologies, metric views, and parameter mappings that ground language models in verified business logic.
• Build robust microservices, REST APIs, and event-driven data pipelines connecting .NET/C# and SQL Server backends with modern Python, FastAPI, Databricks, and Amazon Redshift platforms.
• Partner closely with product managers, UI/UX designers, and frontend engineers to build responsive conversational data experiences featuring smart disambiguation, interactive filters, and full query provenance.
• Put in place enterprise AI guardrails, evaluation suites, and observability frameworks (golden test datasets, prompt defence, token-cost tracking) to guarantee safety, data privacy, and reliability in production.
• Champion modern AI-assisted engineering practices (using tools like Claude Code, Cursor, and Copilot) and create reusable engineering assets (prompts, MCP servers, automation templates) to accelerate team velocity.

What skills do I need

• 8+ years of experience designing, building, and operating enterprise-scale distributed software and cloud systems, demonstrating deep mastery of OOP and modern .NET/C# REST APIs.
• Deep expertise in SQL Server (relational schema design, complex joins, views, and aggregations), along with hands-on experience building scalable data pipelines on Amazon Redshift and Databricks (Delta Lake, Unity Catalog).
• 2+ years of dedicated, hands-on production experience navigating the AI development lifecycle, including LLM orchestration, agentic architectures, contextual retrieval, and non-deterministic system evaluation.
• Advanced proficiency in Python and FastAPI for developing asynchronous microservices, data validation schemas, and enterprise integration gateways.
• Practical experience building Text-to-SQL and NLQ systems, with strong capability in semantic layer architecture and business ontology modelling (metric views, dimensional models, and parameterized functions).
• Experience designing conversational UI workflows (intent disambiguation, active parameter filtering, interactive charting, query lineage drawers).
• Proven hands-on solutions engineering acumen, comfortable operating in ambiguous, client-facing environments to translate business goals into working technical architectures and drive rapid delivery cycles.
• Strong technical leadership experience, with a track record of mentoring senior engineers, leading delivery pods, and clearly explaining complex technical choices to senior executive stakeholders.
• Familiarity with modern frontend frameworks (such as React, Flutter, or Next.js) for delivering responsive data visualization and conversational analytics.

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