Data Architect

Indium • Princeton, CA

1d

About The Position

Data Architect / Data Modeling Lead – Responsibilities Lead the data modernization roadmap and architect solutions aligned with business and technology goals. Design and implement modern data engineering solutions within complex technology landscapes. Develop conceptual, logical, and physical data models across transactional, analytical, operational, and reporting domains, with a strong focus on analytics and reporting. Define, document, and maintain data definitions, metadata, data dictionaries, lineage, and data standards. Perform data analysis and profiling to identify data sources, relationships, quality issues, and gaps. Collaborate with data analysts, engineers, scientists, and business stakeholders to translate business needs into data requirements. Establish and enforce data modeling standards, best practices, and methodologies across the organization. Guide citizen developers on data platform standards and best practices for building data products. Promote reuse of integrated and semantic data objects, minimizing business logic in reports and user -created assets. Drive organization -wide best practices for managing “data as a product.” Partner with application teams to ensure modernized transactional databases follow best practices (e.g., primary keys, core attributes) for seamless integration into the data platform. Introduce and align data governance principles with enterprise data management policies. Assess and manage data warehouse impacts resulting from transactional system modernization. Define and execute plans to migrate legacy data warehouse assets to the modern data platform, including downstream dependencies. Monitor, troubleshoot, and optimize data model performance. Stay current with emerging trends and technologies in data modeling and data management.

Responsibilities

• Lead the data modernization roadmap and architect solutions aligned with business and technology goals.
• Design and implement modern data engineering solutions within complex technology landscapes.
• Develop conceptual, logical, and physical data models across transactional, analytical, operational, and reporting domains, with a strong focus on analytics and reporting
• Define, document, and maintain data definitions, metadata, data dictionaries, lineage, and data standards
• Perform data analysis and profiling to identify data sources, relationships, quality issues, and gaps.
• Collaborate with data analysts, engineers, scientists, and business stakeholders to translate business needs into data requirements.
• Establish and enforce data modeling standards, best practices, and methodologies across the organization.
• Guide citizen developers on data platform standards and best practices for building data products.
• Promote reuse of integrated and semantic data objects, minimizing business logic in reports and user -created assets.
• Drive organization -wide best practices for managing “data as a product.”
• Partner with application teams to ensure modernized transactional databases follow best practices (e.g., primary keys, core attributes) for seamless integration into the data platform.
• Introduce and align data governance principles with enterprise data management policies.
• Assess and manage data warehouse impacts resulting from transactional system modernization.
• Define and execute plans to migrate legacy data warehouse assets to the modern data platform, including downstream dependencies.
• Monitor, troubleshoot, and optimize data model performance.
• Stay current with emerging trends and technologies in data modeling and data management.

What This Job Offers

• Career Level: Mid Level
• Education Level: No Education Listed