Snowflake Data Architect

United States·St. Louismid

Data ArchitectData & AI

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Quick Summary

Overview

At Keeley Companies, we believe in empowering our people and fulfilling career aspirations. Keeley is a career destination with countless opportunities for advancement,

Technical Tools

Data ArchitectData & AI

At Keeley Companies, we believe in empowering our people and fulfilling career aspirations. Keeley is a career destination with countless opportunities for advancement, and a world-class family culture that is centered around creating the best possible environment for our people to thrive.

Keeley Companies is looking to hire a Snowflake Data Architect for our IT Team in St. Louis, MO.

Responsibilities

~2 min read

→Define and execute the target-state Snowflake architecture supporting enterprise reporting, analytics, and decision-making across key business domains.
→Establish enterprise data modeling standards, architectural patterns, governance frameworks, and golden-source strategies.
→Design scalable logical and physical data models for Project Management, HR, Finance, Accounting, Legal, and Operations data domains.
→Develop and maintain a multi-year enterprise data warehouse and data modernization roadmap aligned with business objectives.
→Design AI-ready data architectures that support both structured and unstructured data for advanced analytics and generative AI use cases.
→Establish Snowflake governance standards including security, cost management, performance optimization, data sharing, monitoring, and observability.
→Design and implement Snowflake Cortex capabilities, including AI SQL, LLM functions, document intelligence, vector functions, and Snowpark solutions.
→Lead the development of scalable data ingestion frameworks integrating enterprise applications such as CMiC, UKG, Salesforce, and other critical systems.
→Oversee enterprise data quality, testing, validation, reconciliation, and observability standards.
→Drive Snowflake performance tuning initiatives through query optimization, clustering strategies, workload management, and concurrency scaling.
→Lead large-scale data warehouse modernization and legacy data migration efforts.
→Partner with business and technology leaders to translate complex requirements into scalable data platform solutions.
→Mentor and guide data engineers, analysts, and data scientists in implementing enterprise data architecture and engineering best practices.

Requirements

~2 min read

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field required.
8+ years of enterprise data architecture, data warehousing, and data platform experience.
4+ years of hands-on experience designing and leading Snowflake implementations in cloud production environments.
Proven experience delivering enterprise-scale data warehouse, analytics, and data transformation programs.
Deep expertise in Snowflake architecture, including storage and compute separation, micro-partitioning, clustering, performance tuning, governance, and cost optimization.
Advanced knowledge of dimensional modeling, enterprise data architecture, and data governance best practices.
Strong SQL development skills and experience with modern ELT/ETL tools such as dbt, Fivetran, SSIS, and orchestration platforms.
Experience integrating structured and unstructured data sources, including documents, spreadsheets, emails, and PDFs.
Strong understanding of Microsoft Azure cloud services and enterprise data integration patterns.
Experience implementing Snowflake Cortex, Snowpark (Python), AI SQL, and AI-driven analytics capabilities in production environments.
Experience supporting database administration, data migrations, and modernization initiatives.
Strong leadership, communication, and stakeholder management skills with the ability to present technical strategy to executive audiences.
Demonstrated ability to mentor technical teams and align data platform strategies with long-term business objectives.
SnowPro Advanced Certification preferred.
Experience supporting construction, project-based, HR, finance, accounting, legal, or operations data environments preferred.

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