Lead - AI Data Intelligence (ETL,Azure, SQL, Python, Spark, Data Lakehouse) 7 - 11 years exp from SaaS companies

Zenoti provides an all-in-one, cloud-based software solution for the beauty and wellness industry.

Our solution allows users to seamlessly manage every aspect of the business in a comprehensive mobile solution: online appointment bookings, POS, CRM, employee management, inventory management, built-in marketing programs and more.

Zenoti helps clients streamline their systems and reduce costs, while simultaneously improving customer retention and spending.

Our platform is engineered for reliability and scale and harnesses the power of enterprise-level technology for businesses of all sizes Zenoti powers more than 30,000 salons, spas, medspas and fitness studios in over 50 countries.

This includes a vast portfolio of global brands, such as European Wax Center, Hand & Stone, Massage Heights, Rush Hair & Beauty, Sono Bello, Profile by Sanford, Hair Cuttery, CorePower Yoga and TONI&GUY.

Our recent accomplishments include surpassing a $1 billion unicorn valuation, being named Next Tech Titan by GeekWire, raising an $80 million investment from TPG, ranking as the 316th fastest-growing company in North America on Deloitte’s 2020 Technology Fast 500™.

We are also proud to be recognized as a Great Place to Work CertifiedTM for 2021-2022 as this reaffirms our commitment to empowering people to feel good and find their greatness.

To learn more about Zenoti visit: https://www.zenoti.com 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), would be a plus 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), with exposure to benchmark products like Databricks Genie, or comparable conversational analytics tools would be a plus.

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.

Hands-on familiarity with modern AI-assisted development tools (Cursor, Claude Code, Copilot) combined with the critical engineering judgment needed to audit and validate generated code for enterprise security, ac