About this roleGeneral Information Description: The VP, Snowflake Data Architect will design and build BlackRock's enterprise data warehouse capabilities supporting one or more domains (e.g., HR, Finance, Legal & Compliance). This role is accountable for defining and implementing scalable, secure and regulatory-compliant Snowflake architectures that enable trusted analytics, operational reporting and strategic decision-making across sensitive and highly governed business functions.
This candidate will serve as the senior data architecture authority for one or more domains, establishing enterprise data models, governance frameworks and engineering standards. This individual will partner with senior stakeholders across BlackRock businesses and technology to translate complex regulatory and business requirements into sustainable data platform solutions.
The role requires deep expertise in Snowflake architecture, enterprise data modeling and large-scale data transformation programs.
Key ResponsibilitiesEnterprise Data Architecture & Strategy- Define and execute the target-state architecture for BlackRock's business data domains in Snowflake
- Establish enterprise data modeling standards and architectural patterns
- Design scalable, secure and cost-efficient multi-account Snowflake architectures aligned with BlackRock's enterprise cloud strategy
- Develop data models, conformed dimensions and golden source strategies across regulated domains
- Provide expertise for the development of a multi-year data warehouse transformation roadmap
- Define enterprise architecture patterns for AI-ready data models, ensuring structured and unstructured data are optimized for advanced analytics and generative AI use cases
Snowflake Platform Architecture & Governance- The role includes overseeing definitions for RBAC models, security, dynamic data masking, and secure data sharing, etc.
- Support BlackRock's governance frameworks to ensure legal and regulatory compliance, audit traceability, data lineage and retention policies
- Establish cost governance, performance engineering standards and warehouse optimization strategies
- Define and oversee monitoring, observability and data quality control across the platform
- Design and implement Snowflake Cortex capabilities (LLM functions, AI_SQL, document intelligence and vector functions) to enable secure AI-driven analytics within the HR, Finance and Legal and Compliance domains
- Oversee secure data pipelines to support AI/ML workloads, including vector embeddings, semantic search and unstructured data processing within Snowflake
- Ensuring adherence to BlackRock's governance, access controls and monitoring frameworks for AI-enabled data products
- Integration of Snowflake Native Apps and Snowpark ML capabilities to extend platform intelligence while maintaining enterprise security standards
Data Modeling & Design- Lead logical and physical data model design for one or more business domains, including HR (workforce planning, compensation, payroll), finance (GL, sub-ledger, cost centers, entity hierarchies) and legal & compliance datasets
- Implement SCD strategies, historical tracking models and audit-compliant lineage frameworks
- Evaluate and apply appropriate modeling paradigms
- Ensure traceability of data transformations to support SOX and regulatory reporting controls
Engineering & Delivery Oversight- Oversee the design of scalable ingestion and transformation frameworks leveraging ELT tools (e.g., dbt, Fivetran)
- Establish data testing, validation, reconciliation and observability standards
- Guide orchestration strategies (Airflow or equivalent) for reliable and resilient data pipelines
- Drive performance tuning initiatives using Snowflake query profiling, clustering strategies and concurrency scaling design
Stakeholder Leadership & Operating Model- Serve as the primary technical advisor to business leadership on data strategy
- Lead architecture review boards and set development standards across engineering teams
- Mentor data engineers, fostering technical excellence and architectural consistency
Job RequirementsEducation- Bachelor's degree in computer science, engineering, information systems or related quantitative discipline required
- Advanced degree (Master's or MBA) preferred
- SnowPro Advanced Certification is preferred
Experience- 10+ years of enterprise data architecture and data warehousing experience
- 5+ years designing and leading Snowflake implementations at scale in production environments
- Demonstrated experience designing and delivering enterprise-wide data warehouse solutions
- Proven leadership of large-scale data transformation initiatives within regulated financial services environments
- Experience designing governance, security, and compliance frameworks in cloud-based data platforms
SkillsTechnical Expertise- Deep expertise in Snowflake architecture, including storage/compute separation, micro-partitioning, clustering, performance tuning and cost optimization
- Advanced knowledge of dimensional modeling and enterprise data architecture patterns
- Strong command of SQL and data transformation engineering best practices
- Experience implementing CI/CD pipelines, Infrastructure-as-Code, and DevOps frameworks for data platforms
- Proficiency with modern ELT/ETL tools (dbt / Fivetran preferred), orchestration frameworks and data quality tooling
- Strong understanding of cloud ecosystems (AWS, Azure or GCP) and enterprise data integration patterns
- Experience implementing Snowflake Cortex Snowpark (Python), and AI_SQL capabilities in production environments
- Strong understanding of vector databases, embeddings, semantic search and retrieval-augmented generation (RAG) patterns
- Familiarity with responsible AI frameworks, model governance and secure deployment of LLM-powered enterprise solutions
- Experience enabling AI/ML workloads directly within Snowflake's native ecosystem
Governance & Regulatory- Expertise in data classification, PII handling, row-level security and dynamic masking policies
- Familiarity with SOX controls, audit frameworks, data retention policies and regulatory reporting requirements
- Experience designing end-to-end lineage and traceability frameworks
Leadership & Strategic Capabilities- Ability to define enterprise data strategy and influence senior stakeholders
- Strong executive communication skills, including the ability to present architectural strategy to leadership
- Experience leading architecture governance forums and cross-functional engineering teams
- Demonstrated ability to align technical platforms with long-term business objectives
For PR2-Princeton - 1 University Square Drive Only the salary range for this position is USD$148,000.00 - USD$200,000.00 . Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits. BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance.
Our benefitsTo help you stay energized, engaged and inspired, we offer a wide range of benefits including a strong retirement plan, tuition reimbursement, comprehensive healthcare, support for working parents and Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
Our hybrid work modelBlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities. We remain focused on increasing the impactful moments that arise when we work together in person - aligned with our commitment to performance and innovation. As a new joiner, you can count on this hybrid model to accelerate your learning and onboarding experience here at BlackRock.
Guidance on AI use for candidatesAt BlackRock, AI has long been part of how we work - enhancing decision-making, improving operations, and helping us deliver better outcomes for clients. We encourage candidates to use AI thoughtfully to learn, prepare, and work more effectively; but during our interview process, we want to focus on getting to know you through your own experiences, thinking, and judgment. To support you, we've provided
guidance on when and how to use AI during our hiring process so you can approach each step with confidence and showcase your best self.
