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Semantic Modeling Architect - Atscale
Tiger Analytics · Dallas, United States
Remote · other regionsData Engineering 146 days ago
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About the job
Skills mentioned in this posting (17)
SQLCI/CDAIGitMachine LearningAPIsCloudExcelPower BITableauAnalyticsSnowflakeGenerative AIData ModelingBusiness IntelligenceKPIsData Warehousing
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Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, India, and Singapore, and a substantial remote global workforce.
If you are passionate about leading large-scale cloud and data modernization initiatives that transform enterprise platforms, we would love to hear from you. We are looking for a AtScale Semantic Modeling Architect with 10+ years of experience in enterprise data architecture and financial services. The role will focus on designing, developing, and governing enterprise semantic models using AtScale and SML on Snowflake. The ideal candidate will have strong hands-on experience with AtScale Semantic Layer, SML, Snowflake architecture, semantic modeling, enterprise BI, and banking/financial data.
Responsibilities:
- Design and develop enterprise semantic models using AtScale and SML, including reusable dimensions, hierarchies, measures, metrics, and business definitions.
- Architect and implement AtScale semantic models on Snowflake, leveraging Snowflake's cloud data platform for scalable enterprise analytics.
- Translate complex business requirements into standardized enterprise metrics, KPIs, dimensions, and semantic definitions, ensuring consistency across business and reporting functions.
- Apply dimensional/Kimball modeling principles to create scalable and reusable semantic models supporting multiple business domains.
- Design and optimize Snowflake data models, SQL workloads, and AtScale aggregates to deliver high-performance analytical queries and BI workloads.
- Develop and maintain SML-based semantic definitions, including measures, dimensions, hierarchies, relationships, calculations, and business logic.
- Implement enterprise data security using Snowflake security capabilities, including Row Access Policies, masking policies, role-based access control (RBAC), and Column-Level Security (CLS).
- Integrate and enable governed semantic models for enterprise BI and analytics platforms including Power BI, Tableau, Excel, and other reporting tools.
- Support AI/ML and GenAI use cases through governed semantic metrics and APIs.
- Establish Git-based development, testing, deployment, and CI/CD processes.
- Maintain strong data lineage, governance, auditability, and regulatory compliance.
Requirements
- 10+ years of experience in data architecture, enterprise data warehousing, dimensional modeling, or business intelligence.
- Strong experience in the banking and financial services (BFS) domain.
- 2+ years of hands-on experience with AtScale and SML.
- Strong experience designing and implementing AtScale Semantic Layer solutions.
- Strong hands-on experience with SML (Semantic Modeling Language).
- 2+ years of Snowflake architecture and implementation experience.
- Strong knowledge of Snowflake data architecture, Snowflake SQL, data modeling, performance optimization, and security.
- Strong understanding of dimensional/Kimball modeling and enterprise semantic modeling.
- Advanced SQL development and query optimization skills.
- Experience designing enterprise metrics, KPIs, measures, dimensions, and hierarchies.
- Experience with DAX and/or MDX.
- Experience integrating semantic models with Power BI, Tableau, Excel, or similar enterprise BI platforms.
- Strong understanding of banking data models and financial business processes.
- Experience working with financial, management, risk, or regulatory reporting data.
- Knowledge of Snowflake RBAC, Row Access Policies, masking policies, and Column-Level Security.
- Experience with Git, CI/CD, and automated deployment practices.
- Strong understanding of data governance, lineage, metadata, auditability, and regulatory compliance.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy,
national origin, ancestry, marital status, protected veteran status, disability
status, or any other basis as protected by federal, state, or local law.