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EXL

Senior Manager

Posted Yesterday
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Remote or Hybrid
Hiring Remotely in United States
Senior level
Remote or Hybrid
Hiring Remotely in United States
Senior level
Lead the design and implementation of AI-powered analytics and applications using Snowflake Cortex. Develop semantic models, search and retrieval solutions, agents, AISQL workflows, Snowflake databases, and scalable ETL/ELT pipelines. Optimize performance, security, governance, and data quality while guiding high-impact initiatives and aligning data engineering solutions with organizational goals. Collaborate with technical and business stakeholders and provide executive guidance.
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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)
ResponsibilitiesOversee organizational data engineering solutions. Lead highimpact initiatives. Ensure alignment with organizational goals. Provide executive guidance. QualificationsGraduate in Computer Science, Data Science, or related field. 6-8 years of experience in data engineering or related field.

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