Jobs at Safetrust Inc. (Now Hiring) — 3 open

Role Overview

Safetrust is establishing a new AI & Data Science function to support the next generation of our products, analytics, and AI initiatives. We are seeking an experienced AI & Data Architecture Lead to define and govern the foundation of our enterprise data ecosystem.

This role is responsible for the structure, meaning, quality, governance, and accessibility of product and business data across the organization. The successful candidate will serve as the central authority for data architecture, data modeling, metadata management, and AI data readiness, ensuring that information is organized, trusted, scalable, and optimized for use across operational systems, reporting platforms, and AI technologies.

This position requires a unique combination of technical expertise, business consulting skills, and strategic thinking. The ideal candidate will be equally comfortable discussing business processes with executive leadership, facilitating requirements workshops with stakeholders, and designing scalable data models and governance frameworks.

The role will initially report directly to the VP, Advanced Systems Group and is expected to evolve into a leadership position responsible for building and managing a small team.

Why this Role Matters

Safetrust is investing in AI, analytics, and data-driven decision-making, but those initiatives are only as effective as the quality and structure of the underlying data.

This role will establish the foundation for how data is defined, governed, managed, and consumed across the organization. By creating clear data models, business definitions, governance standards, and AI-ready data structures, the AI & Data Architecture Lead will enable trusted reporting, scalable product development, and future AI capabilities.

The work performed in this role will directly impact the company's ability to leverage data as a strategic asset, support executive decision-making, and accelerate innovation across the business.

Key Responsibilities

Enterprise Data Architecture & Modeling

• Own and maintain the enterprise product data model and underlying database architecture.
• Design, document, and govern conceptual, logical, and physical data models.
• Define standards for data structures, relationships, hierarchies, and data classifications.
• Ensure scalability, consistency, and maintainability across all data assets and platforms.
• Establish and maintain data architecture documentation, including entity relationship diagrams and system mappings.
• Establish and execute plans to migrate existing data into updated models
• Partner with engineering teams to ensure technical implementation aligns with architectural standards.

Data Governance & Stewardship

• Establish and maintain enterprise-wide data governance standards and frameworks.
• Define data ownership, stewardship, accountability, and approval processes.
• Develop policies and standards related to data quality, integrity, retention, classification, and lifecycle management.
• Create governance processes for introducing, modifying, and retiring data elements.
• Ensure critical business data is managed consistently across all systems and applications.
• Partner with Security and Engineering teams to support appropriate data access and control standards.

Data Dictionary, Metadata & Business Glossary Management

• Own and maintain the enterprise data dictionary and business glossary.
• Define and document the meaning, purpose, ownership, and usage of all key data elements.
• Establish metadata standards and governance practices.
• Create a common business language across Product, Engineering, Operations, Sales, Customer Success, and Executive Leadership.
• Ensure consistent definitions and interpretation of data across all systems and reporting platforms.

Semantic Data Design & AI Readiness

• Define the semantic structure of business and product data to support analytics, automation, machine learning, and generative AI initiatives.
• Design data frameworks that support AI-powered search, recommendation engines, knowledge retrieval, and future AI applications.
• Develop strategies for organizing structured and unstructured data for AI consumption.
• Ensure data models support future AI and machine learning capabilities while maintaining governance and quality standards.
• Evaluate opportunities to leverage semantic modeling, knowledge graphs, and advanced metadata frameworks where appropriate.

Snowflake & Data Platform Strategy

• Lead the design and governance of data flows into Snowflake and future enterprise data platforms.
• Define standards for data ingestion, transformation, storage, and consumption.
• Collaborate with Engineering teams on ETL/ELT design and implementation.
• Ensure data pipelines support business reporting, operational analytics, and AI use cases.
• Monitor scalability and long-term platform sustainability.

Data Quality & Master Data Management

• Establish data quality standards, monitoring practices, and remediation processes.
• Develop controls to reduce duplication, inconsistencies, and conflicting definitions.
• Define and maintain master data management practices for critical business entities.
• Implement validation standards and quality metrics across key datasets.
• Partner with stakeholders to resolve data integrity issues and drive continuous improvement.

Business Partnership & Consulting

• Act as a strategic advisor to executive leadership on data strategy and governance initiatives.
• Facilitate workshops and discovery sessions to identify business requirements and data needs.
• Translate business concepts into scalable data structures, relationships, and models.
• Partner with Product, Engineering, Operations, and Customer-facing teams to ensure data solutions support organizational objectives.
• Provide recommendations for improving data maturity, reporting capabilities, and AI readiness.

Team Leadership & Growth

• Assist in establishing and growing the AI & Data Science function.
• Mentor future team members and establish standards, methodologies, and best practices.
• Support recruitment and development of future data architecture and governance resources.
• Promote a culture of data stewardship, accountability, and continuous improvement.

Qualifications

Required:

• Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Business Analytics, or a related field.
• 5+ years of experience in Data Architecture, Data Governance, Enterprise Data Management, Business Intelligence, Analytics, or related disciplines.
• Advanced experience designing conceptual, logical, and physical data models.
• Strong understanding of relational databases, data warehouses, and modern cloud-based data platforms.
• Experience implementing data governance frameworks and metadata management practices.
• Experience creating and maintaining enterprise data dictionaries and business glossaries.
• Strong understanding of data quality management and master data management principles.
• Experience working with Snowflake, BigQuery, Databricks or similar enterprise data platforms.
• Strong SQL and data analysis skills.
• Experience supporting analytics, reporting, and AI-driven data initiatives.
• Exceptional written and verbal English communication skills.
• Ability to communicate effectively with executive leadership, technical teams, and business stakeholders.
• Strong consulting, facilitation, and stakeholder management capabilities.

Preferred:

• Experience supporting machine learning, generative AI, or AI-enabled product initiatives.
• Experience with semantic modeling, ontology design, knowledge graphs, or metadata-driven architectures.
• Experience with data cataloging and governance tools.
• Experience in SaaS, enterprise software, cybersecurity, identity management, or access control industries.
• Experience building and leading data teams.
• Experience working within global organizations supporting multiple regions and cultures.

Safetrust is an equal opportunity employer and prohibits discrimination and harassment of any kind. We offer an inclusive workplace and will not tolerate discrimination against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status or parental status.