Semantic Modeling Architect

Job not on LinkedIn

🔥 4 hours ago

🏖️ New Jersey – Remote

🏖️ New Jersey – Remote

⏰ Full Time

🟠 Senior

🔴 Lead

🏛️ Architect

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Tiger Analytics

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2011

🏥 Healthcare

📦 Logistics

📣 Marketing

Healthcare • Logistics • Marketing

Tiger Analytics is a leading AI and analytics consulting firm that specializes in leveraging data science and machine learning to provide strategic business insights across various industries. They offer services in data strategy, AI engineering, and business intelligence to enable data-driven decision-making and digital transformation for their clients. Tiger Analytics collaborates with top technology partners like Microsoft, Google Cloud, and AWS to deliver cutting-edge solutions. They serve a diverse range of sectors including consumer packaged goods, healthcare, and finance, helping businesses operationalize insights and differentiate with AI and machine learning technologies.

📋 Description

• 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 for scalable enterprise analytics • Translate complex business requirements into standardized enterprise metrics, KPIs, dimensions, and semantic definitions • Apply dimensional/Kimball modeling principles across multiple business domains • Design and optimize Snowflake data models, SQL workloads, and AtScale aggregates for 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 Row Access Policies, masking policies, RBAC, and Column-Level Security • Integrate governed semantic models with 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 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

• Medical, Dental, Vision • Retirement Accounts • Long and Short Term Disability • Life Insurance • HSA/FSA Accounts (USA) • Discretionary time-off • Lead strategic engagements delivering enterprise-wide AI adoption, cloud-native data modernization, and measurable business outcomes • Collaborate with exceptional AI, data, engineering, and consulting talent across geographies • Continuous learning and hands-on exposure to emerging technologies • Opportunities to build expertise in Generative AI, agentic AI, and next-generation data platforms • Career growth with a team that invests in developing future-ready skills and encourages innovation

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