Director, Senior Information Architect

Harnham; Los Angeles (CA); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Competitive benefits

Shape enterprise data platform

Executive exposure

Job summary

Harnham is seeking a Senior Information Architect in Los Angeles to lead the design and evolution of enterprise data architecture across a rapidly growing environment. The role requires owning architecture decisions, influencing strategy, and partnering with technical and business stakeholders to review data models, pipelines, and engineering solutions, with a focus on analytics and AI capabilities.

You will establish standards for data governance, security, and metadata management, architect

Qualifications

• Deep expertise in dimensional modeling, Kimball methodologies, and star schema design.
• Strong data governance experience.
• Experience designing data security and privacy frameworks.
• Experience building modern cloud-based data platforms.
• Ability to translate business objectives into architectural solutions.
• Strong stakeholder management and communication skills.
• Technical proficiency in Python, SQL, and Scala sufficient to review engineering work.
• Proven ability to partner effectively with Data Engineering teams.
• Experience operating independently and influencing senior leadership.

Responsibilities

• Define enterprise data architecture standards and best practices.
• Lead data modeling initiatives utilizing dimensional modeling, Kimball methodologies, and star schema design.
• Architect Databricks Lakehouse environments and platform standards
• Create governance, security, privacy, and compliance frameworks across the data ecosystem.
• Design data ingestion, orchestration, and transformation strategies.
• Drive data platform modernization and migration initiatives.
• Establish scalable metadata and catalog management structures.
• Partner with engineering teams to review architecture, pipelines, and implementation approaches.
• Work with business stakeholders to translate business challenges into scalable technical solutions.
• Support analytics, reporting, AI, and machine learning initiatives through strong architectural foundations.

Skills

Dimensional modeling

Kimball methodologies

Star schema design

Data governance

Data security & privacy

Cloud data platforms

Python

SQL

Scala

Stakeholder management

Tools

Databricks

Databricks Unity Catalog

Job description

Our client is a large-scale investment and asset management organization undergoing significant growth and modernization across its data and technology ecosystem. With technology now viewed as a strategic business driver, the company is making major investments in enterprise data architecture, governance, analytics, and AI capabilities.

About the Role

We are seeking a Senior Information Architect to lead the design and evolution of enterprise data architecture across a complex and rapidly growing environment.

This is a senior individual contributor role for someone who enjoys owning architecture decisions, influencing enterprise strategy, and partnering closely with technical and business stakeholders. While not a day-to-day coding position, candidates must possess the technical depth to review architecture, data models, pipelines, and engineering solutions across modern data platforms.

This position will play a critical role in defining how data is structured, governed, secured, and leveraged for analytics and AI initiatives.

What You'll Do

• Define and establish enterprise data architecture standards and best practices
• Lead data modeling initiatives utilizing dimensional modeling, Kimball methodologies, and star schema design
• Architect Databricks Lakehouse environments and platform standards
• Create governance, security, privacy, and compliance frameworks across the data ecosystem
• Design data ingestion, orchestration, and transformation strategies
• Drive data platform modernization and migration initiatives
• Establish scalable metadata and catalog management structures
• Partner with engineering teams to review architecture, pipelines, and implementation approaches
• Work with business stakeholders to translate business challenges into scalable technical solutions
• Support analytics, reporting, AI, and machine learning initiatives through strong architectural foundations

Key Projects

• Enterprise Databricks migration and platform modernization
• Development of Lakehouse and medallion architecture standards
• Enterprise-wide governance and security framework implementation
• Large-scale data modeling and information architecture initiatives
• Creation of scalable metadata, catalog, and business glossary structures
• Supporting AI and advanced analytics capabilities through enterprise data architecture

Must-Have Qualifications

• Deep expertise in dimensional modeling, Kimball methodologies, and star schema design
• Strong data governance experience
• Experience designing data security and privacy frameworks
• Experience building modern cloud-based data platforms
• Ability to translate business objectives into architectural solutions
• Strong stakeholder management and communication skills
• Technical proficiency in Python, SQL, and Scala sufficient to review engineering work
• Proven ability to partner effectively with Data Engineering teams
• Experience operating independently and influencing senior leadership

Nice-to-Have Qualifications

• Databricks Unity Catalog experience
• Medallion architecture expertise
• AI/ML or GenAI platform architecture exposure
• Hadoop or Apache ecosystem experience
• Data platform migration leadership experience
• Consulting experience leading enterprise transformation programs
• Experience within financial services, banking, insurance, private equity, asset management, or other highly regulated industries

Ideal Candidate

The strongest candidates will demonstrate ownership of enterprise-scale architecture decisions, governance strategies, and platform transformations. They should be able to clearly explain not only what they built, but why architectural decisions were made and how those decisions aligned to business goals, governance requirements, and security standards.

• Competitive benefits package
• Opportunity to shape the future state of a growing enterprise data platform
• High visibility and executive stakeholder exposure