About this roleVice President - Lead Data Engineer (Data Cloud Platform)The Vice President - Lead Data Engineer will drive the strategy, architecture, and delivery of next-generation data engineering capabilities on the enterprise Data Cloud Platform. This role is responsible for building scalable, governed, and event-driven data ecosystems that power investment, analytics, and reporting platforms with high-quality, near real-time data.
Role Overview- Lead the design and delivery of enterprise-grade data pipelines and domain-oriented data products.
- Champion modern data architecture patterns, including event-driven and streaming frameworks.
- Establish and enforce data-as-a-product principles, standardized data models, and governance frameworks.
- Serve as a senior technical leader partnering across engineering, product, and platform organizations.
Key Responsibilities- Define and execute the data engineering strategy for batch and real-time pipelines, ensuring scalability, reliability, and cost efficiency.
- Lead development of event-driven architectures leveraging streaming platforms (e.g., Kafka) and modern processing frameworks.
- Drive enterprise data modeling standards (conceptual, logical, physical) and promote reusable, domain-aligned data products.
- Establish robust data governance, quality, lineage, and observability practices across the platform.
- Oversee end-to-end data lifecycle management, from ingestion through consumption and archival.
- Partner with cross-functional teams to align platform capabilities with business and investment use cases.
- Promote engineering excellence through CI/CD, automation, and standardized development practices.
Leadership & Impact- Provide technical leadership, mentorship, and direction to high-performing data engineering teams.
- Influence enterprise architecture and platform strategy decisions.
- Drive adoption of scalable, reusable, and standardized data solutions across the organization.
- Ensure alignment between data engineering initiatives and business outcomes, particularly in financial services and investment domains.
Qualifications- Extensive experience in data engineering, distributed systems, and modern data platforms (e.g., Snowflake).
- Strong expertise in SQL and programming (Python, Java, or Scala).
- Proven track record of building and scaling production-grade data platforms and pipelines.
- Experience with streaming and event-driven architectures.
- Deep understanding of data modeling, governance, and data quality frameworks.
- Prior experience in financial services or asset management preferred.
For New York, NY Only the salary range for this position is USD$162,000.00 - USD$215,000.00 . 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.
