Senior Manager @ EXL

Core Responsibilities

AI & Snowflake Cortex Responsibilities

• AI Solution Design & Implementation: Build AI‑powered analytics, semantic insights, and business applications using Snowflake Cortex capabilities.
• Semantic Models & Views: Develop and maintain semantic layers enabling natural language querying, governed metrics, and business‑friendly data access.
• Cortex Search & Knowledge Retrieval: Design and optimize enterprise search solutions for document intelligence and knowledge retrieval.
• Cortex Agents: Configure and orchestrate agents to unify structured and unstructured data sources for automated workflows.
• AISQL Functions: Implement summarization, classification, extraction, sentiment analysis, and content generation use cases.
• AI Application Development: Build interactive AI applications using Streamlit, Snowsight, and Python frameworks within Snowflake.
• Testing & Improvement: Validate, monitor, and continuously enhance AI models, agents, and applications.

General Snowflake Development Responsibilities

• Database Design & Management: Create and manage Snowflake databases, schemas, tables, and objects for efficient, organized data storage.
• SQL Development: Write complex SQL queries to extract, transform, and load (ETL/ELT) data for analytics, reporting, and AI workflows.
• Data Pipeline Development: Build and maintain scalable ETL/ELT pipelines to ingest data from diverse sources into Snowflake with high quality and reliability.
• Performance Optimization: Monitor and optimize Snowflake performance through query tuning, clustering, micro‑partitioning, and workload scaling.
• Security & Access Control: Implement RBAC, data governance, user permissions, and security policies to protect sensitive information.
• Collaboration: Work closely with data engineers, analysts, architects, and business teams to translate requirements into scalable data and AI solutions.
• Testing & Documentation: Conduct unit testing, code reviews, and maintain clear documentation for data workflows, pipelines, and AI applications.

Required Skills & Experience

Snowflake & AI Expertise

• Hands‑on experience with Snowflake Cortex: Cortex Analyst, Cortex Search, Cortex Agents, AISQL Functions, Semantic Models.
• Strong understanding of Snowflake’s CoCO, Snowpark, and platform‑native AI capabilities.

Technical Skills

• Proficiency in SQL, Python, and ETL/ELT tools ( Informatica, dbt etc.).
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with Spark, Kafka, and modern data engineering frameworks.

Data Warehousing & Modeling

• Strong knowledge of dimensional modeling(star Schema), semantic modeling, data architecture, and analytical data design.
• Experience integrating AI/ML patterns into enterprise data platforms.

Generative AI & LLMs

• Experience with prompt engineering, RAG architectures, embeddings, and agent design.
• Understanding of LLM‑driven workflows and enterprise AI application patterns.

Soft Skills

• Strong problem‑solving abilities and analytical thinking.
• Effective communication with technical and non‑technical stakeholders.
• Ability to work collaboratively and take ownership of projects.

Certifications (Preferred)

• Snowflake Certified Developer / SnowPro
• Cloud certifications (AWS, Azure, GCP)

Oversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance.

Graduate in Computer Science, Data Science, or related field. 6-8 years of experience in data engineering or related field.