Data Acquisition Engineering Lead, Vice-President

About this role

About BlackRock

At BlackRock, technology is at the core of everything we do. Our technologists shape the future of the industry through innovation, collaboration, and a willingness to experiment to solve complex challenges. We foster an environment that promotes cross-functional teamwork and supports your growth through curated learning opportunities, tech-specific career paths, and access to experts and leaders worldwide.

Private markets are a critical growth area for BlackRock, and our mission is to make them more accessible and transparent for clients. The Private Markets Data Engineering team plays a pivotal role in building scalable, reliable data platforms and pipelines that power insights and investment decisions across the firm.

Role Overview

As Vice President, Private Markets Data Engineering, you will lead a high-performing engineering team responsible for designing and delivering robust, scalable data solutions for private markets. This role combines deep technical expertise with strategic leadership, ensuring our data architecture and pipelines meet evolving business needs while driving innovation and operational excellence.

• Technical Leadership & Strategy
  
  • Define and execute the technical vision for Private Markets Data Engineering, aligning with BlackRock's broader data strategy.
  • Lead architectural discussions on data modeling, orchestration, and platform scalability.
  • Champion best practices for engineering quality, testing, security, and observability.
• Data Platform & Pipeline Development
  
  • Design and implement scalable, reliable data pipelines using Python, Java, SQL, and modern frameworks (Apache Airflow, Temporal).
  • Build APIs and backend services for data distribution and consumption, optimizing for performance and resilience.
  • Integrate AI/ML workflows with human expertise to accelerate data collection and improve decision-making.
• Operational Excellence
  
  • Ensure data quality and integrity through automated validation tools (e.g., Great Expectations).
  • Monitor and troubleshoot data workflows, implementing observability and performance optimization.
  • Drive adoption of infrastructure-as-code and CI/CD practices for efficient deployments.
• Collaboration & Stakeholder Engagement
  
  • Partner with product, data research, and program management teams to deliver outcome-based solutions.
  • Influence technical decisions across engineering pods and share knowledge to elevate development standards.

• Experience
  
  • 9+ years in software/data engineering, with at least 3+ years in a leadership role.
  • Proven track record of designing and delivering large-scale data platforms and pipelines.
• Technical Expertise
  
  • Strong programming skills in Python and/or Java; experience with backend microservices and APIs.
  • Proficiency in orchestration tools (Apache Airflow), data transformation (DBT), and data validation frameworks.
  • Hands-on experience with relational (PostgreSQL, Snowflake) and NoSQL databases (MongoDB, Elasticsearch).
  • Familiarity with distributed computation frameworks (Apache Spark) and container orchestration (Kubernetes).
  • Cloud experience (AWS and/or Azure) and infrastructure-as-code (Terraform) knowledge.
• Leadership & Communication
  
  • Ability to lead technical teams, influence stakeholders, and drive strategic initiatives.
  • Excellent verbal and written communication skills; ability to bridge technical and business perspectives.
• Preferred
  
  • Experience in financial services or private markets.
  • Exposure to AI/ML-driven data workflows.
  • Knowledge of CI/CD pipelines and modern DevOps practices.