Senior Data Architect

We are seeking a Principal / Senior Data Architect to lead the design and evolution of Pretium's modern enterprise data platform that powers analytics, investment decisioning, and operational intelligence across our real estate portfolio.

This is a hands-on architecture leadership role responsible for defining enterprise data architecture, modern data platform strategy, and domain-driven data models across large-scale real estate and financial data ecosystems.

You will partner with engineering, analytics, and business leaders to build a scalable, cloud-native data platform using technologies such as Snowflake, AWS, Python, and modern ELT frameworks, while driving adoption of modern architectural patterns such as Data Mesh, Lakehouse architecture, and data-as-a-product principles.

What You Will Do

Architect the Enterprise Data Platform

• Define and evolve the enterprise data architecture supporting large-scale real estate investment and operational data.
• Architect a modern cloud-native data platform leveraging Snowflake and AWS.
• Design Lakehouse-style architectures combining structured, semi-structured, and unstructured data.
• Build scalable data platforms capable of supporting:
• portfolio analytics
• property performance
• mortgage servicing analytics
• financial modeling
• AI/ML use cases.

Design Domain-Centric Data Architecture

• Develop domain-driven data models for key business domains such as:
• Property & asset lifecycle
• Rental operations
• Mortgage servicing
• Portfolio & investment analytics
• Customer and tenant data
• Implement data product architecture aligned with Data Mesh principles.
• Establish reusable data modeling standards including dimensional modeling, data vault, and semantic layers.

Lead Modern Data Engineering Architecture

• Architect scalable ELT data pipelines for ingesting data from operational systems, financial platforms, and third-party real estate datasets.
• Define architecture patterns for:
• batch and real-time ingestion
• streaming pipelines
• event-driven architectures
• metadata-driven transformations.
• Enable self-service analytics platforms and scalable BI ecosystems.

Hands-on Architecture Leadership

• Provide hands-on technical leadership across architecture and engineering teams.
• Review and guide implementation of:
• data pipelines
• Snowflake warehouse design
• data modeling strategies
• performance optimization.
• Establish reference architectures, engineering standards, and reusable frameworks.

Data Governance, Quality & Security

• Define enterprise data governance frameworks covering:
• metadata management
• data catalog
• lineage
• data quality monitoring
• Implement enterprise data security including:
• role-based access control
• data masking
• regulatory compliance frameworks (GDPR, CCPA).
• Ensure high standards of data reliability, observability, and trust.

Drive Platform Innovation

• Evaluate emerging technologies across the modern data stack.
• Introduce capabilities such as:
• data observability platforms
• automated data quality monitoring
• ML-ready feature stores
• real-time analytics.
• Partner with analytics teams to enable AI/ML and advanced analytics platforms.

What will an Ideal Candidate Profile look like

You are a hands-on data platform architect who has built and scaled enterprise data platforms in cloud environments and understands how data enables business decision-making at scale.

You combine deep technical expertise with business understanding, especially in real estate, financial services, or asset management domains.

Required Experience

• 15+ years of experience in Data Architecture, Data Engineering, or Enterprise Data Platforms.
• Proven experience designing enterprise-scale data platforms on Snowflake or similar cloud warehouses.
• Hands-on experience architecting modern data platforms on AWS or other cloud environments.
• Experience working with large-scale financial, real estate, or investment data ecosystems preferred.
• Strong experience implementing modern data architecture frameworks.

Core Technical Skills

Data Platform Architecture

• Snowflake architecture and performance optimization
• Lakehouse architectures
• Data mesh and data product design
• Enterprise data modeling

Data Engineering

• Python
• SQL (advanced)
• ELT frameworks
• Orchestration tools (Airflow or equivalent)

Cloud Platforms

• AWS data ecosystem (S3, Glue, Lambda, IAM)
• Infrastructure as Code (Terraform / CloudFormation)
• Scalable distributed data processing

Analytics Platforms

• Semantic layers and BI tools (Looker / Power BI)
• Data marts and analytical models

Data Governance

• Metadata management
• Data lineage
• Data quality frameworks
• Data security and privacy

Leadership & Influence

• Ability to influence enterprise architecture strategy.
• Experience mentoring architects and senior engineers.
• Strong stakeholder management with both technical and business leaders.
• Track record of driving data platform modernization initiatives.

Preferred Qualifications

• Snowflake Certified Architect / Data Engineer
• AWS Certified Solutions Architect
• Experience implementing Data Mesh or Lakehouse platforms
• Exposure to AI/ML data platform design