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
