Senior Data Architect

Tyler Technologies, Inc.; Philippines; On-site; PHP 4,500,000 - 7,500,000; Full time

Job summary

Tyler Technologies, Inc. seeks a Senior Data Architect to lead the design of a modern medallion-architecture data platform and dimensional models powering analytics across the enterprise.

This hands-on individual contributor role focuses on star schemas and robust ELT pipelines transforming enterprise data into trusted analytical assets. The role owns Silver and Gold layer design, conformed dimensions, and fact tables, and shapes data governance, quality, and security embedded in models and

Qualifications

• Bachelor’s degree in CS/IS/engineering or related field.
• 10+ years of data engineering/architecture experience.
• Expert-level dimensional modeling (Kimball): conformed dimensions, fact table grain, slowly changing dimensions, and star schema design.
• Hands-on experience architecting solutions on modern cloud data platforms (Azure, AWS, Microsoft Fabric, Databricks, or Snowflake) with strong SQL and large-scale data transformations.
• Proven, hands-on experience designing and building ETL/ELT pipelines from structured enterprise source systems.
• Demonstrated ability to design reusable, shared dimensional models that serve multiple downstream fact tables and analytics use cases.

Responsibilities

• Architect and design the end-to-end medallion architecture (Bronze, Silver, Gold), with primary ownership of Silver and Gold layer design.
• Design dimensional models (star schemas) following Kimball methodology, including conformed/shared dimensions and fact tables that integrate across multiple subject areas.
• Define and build ETL/ELT patterns to transform raw source data into clean, conformed dimensions and analytics-ready fact tables.
• Establish data modeling standards, naming conventions, and reusable design patterns for shared dimensions used across multiple fact tables.
• Architect ingestion and transformation from enterprise source systems into the platform, designing for source-system schema and synchronization behavior.
• Translate business and analytical requirements into durable, scalable data models and source-to-target mappings.
• Embed data governance, quality, security, and regulatory compliance into model and pipeline design.
• Lead technical design reviews, set best practices, and provide deep technical guidance to data engineers.
• Ensure data quality, integrity, and performance across the Silver and Gold layers.
• Demonstrated ability to solve highly complex enterprise data architecture challenges.
• Accountable for the integrity, scalability, and reusability of the Silver and Gold data models that serve enterprise analytics.

Skills

Dimensional modeling

Kimball methodology

Star schema design

Conformed dimensions

Fact tables

Slowly changing dimensions

SQL

Education

Bachelor's degree in computer science, information systems, engineering, or a related field

Tools

Azure

AWS

Microsoft Fabric

Databricks

Snowflake

Job description

The Senior Data Architect leads the design of a modern, medallion-architecture data platform and the dimensional models that power enterprise analytics. This is a hands-on, deep-technical individual contributor role focused on architecting scalable star schemas and robust ELT pipelines that transform structured data from enterprise systems into trusted, reusable analytical assets. The role owns the architecture of the Silver and Gold layers, designing conformed dimensions and fact tables that serve analytics needs across the organization. This is a senior individual contributor role — it carries deep architectural ownership and influence without direct people-management responsibilities.

Responsibilities

• Architect and design the end-to-end medallion architecture (Bronze, Silver, Gold), with primary ownership of Silver and Gold layer design.
• Design dimensional models (star schemas) following Kimball methodology, including conformed/shared dimensions and fact tables that integrate across multiple subject areas.
• Define and build ETL/ELT patterns to transform raw source data into clean, conformed dimensions and analytics-ready fact tables.
• Establish data modeling standards, naming conventions, and reusable design patterns for shared dimensions used across multiple fact tables.
• Architect ingestion and transformation from enterprise source systems (e.g., Microsoft Dynamics 365 Finance & Operations, Customer Engagement, Project Operations, NICE CXone, Atlassian JSM / Jira / Confluence, Ramp, etc…) into the platform, designing for source-system schema and synchronization behavior.
• Translate business and analytical requirements into durable, scalable data models and source-to-target mappings.
• Embed data governance, quality, security, and regulatory compliance (including data privacy requirements) into model and pipeline design, working with relevant stakeholders to uphold standards.
• Lead technical design reviews, set best practices, and provide deep technical guidance to data engineers.
• Ensure data quality, integrity, and performance across the Silver and Gold layers.
• Expert-level command of dimensional modeling and the ability to design conformed, reusable models that resolve competing requirements across multiple subject areas.
• Demonstrated ability to solve highly complex enterprise data architecture challenges.
• Accountable for the integrity, scalability, and reusability of the Silver and Gold data models that serve enterprise analytics. Architectural decisions made in this role directly shape the reliability of downstream reporting and analytics across multiple business domains.

Qualifications

• Bachelor’s degree in computer science, information systems, engineering, or a related field.
• 10+ years of experience in data engineering / data architecture roles.
• Expert-level command of dimensional modeling (Kimball methodology): conformed dimensions, fact table grain, slowly changing dimensions, and star schema design
• Hands-on experience architecting solutions on a modern cloud data platform (e.g., Azure, AWS, Microsoft Fabric, Databricks, or Snowflake), plus strong SQL skills and experience building large-scale data transformations.
• Proven, hands-on experience designing and building ETL/ELT pipelines from structured enterprise source systems.
• Demonstrated ability to design reusable, shared dimensional models that serve multiple downstream fact tables and analytics use cases.

Preferred Qualifications

• Experience with Microsoft Fabric, Databricks, or Snowflake.
• Experience modeling data sourced from Microsoft Dynamics 365 Finance & Operations, CE, Project Operations.
• Power BI and semantic model design experience.
• Data governance and master data management (MDM) experience.