# AI Data Enablement Engineer

> Xenon7 · Hyderabad, India (Hybrid) · — · Posted 2026-08-23

**Workplace:** hybrid

**Department:** Novartis

## Description

Our Client's Digital Finance IT is building an AI-enablement layer on top of our enterprise data platform to enable business users across Finance to interact with governed data in natural language. We're hiring a **Data Enablement Engineer** to design, build, and operate the trusted datasets, semantic models, and embedded AI experiences that make this possible.

This is a **data platform engineering role**, not a data science or model-building role. You will spend your time engineering the data foundation that makes AI reliable — semantic layers, governed data products, and embedded natural-language analytics — not training models.

**What You'll Do**

-   Design and build **AI-ready data products** on Snowflake and/or Databricks — trusted datasets with well-defined business semantics, KPIs, hierarchies, and business glossary alignment
-   Implement **semantic layers** and governed datasets that support both traditional BI consumption and natural-language querying by business users
-   Deploy and operate **Snowflake Cortex** capabilities (Cortex Analyst, Cortex Search, Cortex Agents, Cortex LLM Functions) and/or **Databricks Genie spaces** with Unity Catalog, tuning them for accuracy, adoption, and business relevance
-   Build **RAG pipelines and conversational analytics applications** grounded in governed enterprise data — including Streamlit or Databricks Apps that let business users query data without writing SQL
-   Engineer robust ETL/ELT pipelines (dbt, Airflow, Snowpark, PySpark) that produce and maintain the trusted data these AI experiences depend on
-   Implement **data governance** — RBAC, row/column-level security, masking, lineage, auditability, catalog and metadata management — in a regulated pharma environment
-   Optimize **cost and performance** on both the data platform side (warehouse sizing, cluster tuning, query optimization) and the AI side (token usage, caching, model routing)
-   Partner with Finance business stakeholders to translate domain requirements into semantic models and governed data products they can trust

## Requirements

**Must-Have Experience**

-   **5+ years hands-on data engineering** on cloud data platforms — Snowflake and/or Databricks demonstrated in real project delivery, not skill-list-only
-   **Direct hands-on experience with either Snowflake Cortex or Databricks Genie** — you have built, configured, and tuned these in production or advanced pilots, with specific reference to the flavors used (Cortex Analyst / Search / Agents / LLM Functions, or Genie spaces with semantic models)
-   **Semantic layer / trusted data product delivery** — you have built governed datasets that business users can rely on, with KPI definitions, hierarchies, and business glossary alignment
-   **dbt, PySpark, Snowpark, SQL, Python** — strong across the modern data stack
-   **Orchestration** with Airflow, Databricks Workflows, or equivalent
-   **Data governance in regulated environments** — RBAC, RLS, masking, lineage, auditability
-   Experience integrating **structured and unstructured data** (PDFs, SharePoint/Teams content, enterprise knowledge sources) into AI-enablement workflows

**Nice to Have**

-   Pharma, life sciences, or regulated financial services domain experience
-   Veeva CRM, IQVIA, SAP, or clinical data source integration
-   Streamlit or Databricks Apps for business-facing analytics
-   SnowPro Advanced or Databricks Data Engineer Professional certification
-   LangChain, LlamaIndex, or equivalent RAG frameworks
-   Cost optimization on both compute (warehouse/cluster) and LLM (tokens/caching/routing) dimensions

**What We're NOT Looking For**

-   **Data Scientists** — this role is not model training, fine-tuning, LoRA/RLHF, or ML research
-   **Pure Data Engineers** who list Cortex or Genie as a skill but haven't shipped it in production
-   **AI/GenAI engineers** whose center of gravity is LangChain agents or RAG-over-documents, without a strong governed data platform foundation
-   **Computer vision, NLP model builders, or multi-agent orchestration specialists** — wrong shape for this role

## Apply

[Apply at Xenon7](https://apply.workable.com/xenon7/j/3DEF6901BB/apply)

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