Level

BlackRock

VP - Senior Data Engineer

AI in this role

ragai-agents

About this role

About the Role  

This position sits within BlackRock’s Private Markets Data Engineering (PMDE) team, at the heart of our mission to revolutionize private markets data and technology.  

As Vice President, you will play a pivotal role in building and scaling our data infrastructure and analytics capabilities as a senior individual contributor and hands-on technical leader. You will work closely with business stakeholders to translate strategic objectives and user needs into actionable data initiatives and technical solutions, operating with direct line management while retaining accountability for technical outcomes.  

In addition to modern data engineering practices, this role will help shape the next generation of AI-enabled data platforms, including semantic data models, knowledge graph capabilities, metadata-driven architectures, and intent-based data access layers that power AI agents, copilots, and intelligent applications. 

 

Key Responsibilities  

  • Provide hands-on technical leadership across the PMDE team, acting as a technical authority for data architecture and engineering decisions. Lead the design and implementation of AI-ready data platform capabilities including semantic data layers, knowledge graph platforms, vector stores, and metadata-driven architectures. 

  • Define and evolve business semantic models, measures, dimensions, ontologies, and governed data products that provide consistent data access across analytics, applications, APIs, and AI workloads. 

 

  • Architect knowledge graph solutions and graph data models that capture complex business relationships and support entity resolution, relationship intelligence, and multi-hop reasoning use cases. 

 

  • Build intent-driven data access patterns that enable AI assistants, agents, and applications to dynamically route requests across structured data, semantic models, graph databases, and unstructured content repositories. 

 

  • Design and develop scalable, reliable data pipelines and analytics platforms, with accountability for end-to-end technical design, data, and long-term sustainability, with a strong focus on Snowflake, SQL, and Python.  

  • Influence technical prioritization and solution design based on business impact and strategic alignment, partnering with product and engineering leads. 

  • Engage and communicate complex technical concepts to management including making clear architectural recommendations. 

  • Collaborate with business stakeholders to translate strategic objectives into actionable data initiatives, ensuring alignment with Preqin’s and BlackRock’s broader vision.  

  • Champion best practices in data management, governance, and security, leveraging automation, cloud technologies, and modern engineering principles.  

  • Oversee technical delivery and architectural coherence across initiatives, prioritizing work based on data-driven insights and business outcomes.  

  • Promote a collaborative environment, bridge the gap between technical and business teams.  

  

Qualifications: 

  • Proven experience in senior technical roles, with deep hands-on expertise in Snowflake, SQL, and Python.  

  • Demonstrated leadership experience in senior technical roles, including leading complex initiatives and providing technical direction to other engineers, with or without direct line management.  

  • Experience designing and implementing semantic data models, business ontologies, data products, and metadata-driven architectures. 

  • Hands-on experience with Graph Database technologies (Neo4j or equivalent) and graph modeling patterns. 

  • Experience building AI-ready data platforms leveraging vector databases, document retrieval systems, and Retrieval-Augmented Generation (RAG) architectures. 

  • Strong understanding of enterprise metadata management, data catalogs, lineage, governance, and business glossary concepts. 

 

  • Experience integrating Large Language Models (LLMs), AI agents, copilots, or agentic workflows with enterprise data platforms. 

  • Deep understanding of data architecture, pipeline design, pipeline tooling (e.g, Airflow, DBT, Snowflake), and cloud platforms (Azure or AWS preferred).  

  • Demonstrated ability to engage and influence stakeholders at all levels, with exceptional communication and interpersonal skills.  

  • Experience translating business requirements into scalable technical solutions.  

  • Comfortable operating in a fast-paced, dynamic environment, balancing long-term technical direction with immediate delivery needs.   

Nice to Have  

  • Experience working with global teams and multi-language environments.  

  • Exposure to Kubernetes and advanced observability practices.  

  • Working knowledge of the financial services sector and private capital markets such as private equity, real estate, and infrastructure.  

Our benefits

To 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 model

BlackRock’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 candidates


At 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.


About BlackRock


At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being.  Our clients, and the people they serve, are saving for retirement, paying for their children’s educations, buying homes and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.


This mission would not be possible without our smartest investment – the one we make in our employees. It’s why we’re dedicated to creating an environment where our colleagues feel welcomed, valued and supported with networks, benefits and development opportunities to help them thrive.


To learn more about BlackRock, please visit Careers.BlackRock.com. We also encourage you to get to know us on LinkedIn, Instagram, YouTube, X, and TikTok.

BlackRock is proud to be an Equal Opportunity Employer.  We evaluate qualified applicants without regard to age, disability, family status, gender identity, race, religion, sex, sexual orientation and other protected attributes at law.

How we rate this

VP - Senior Data Engineer at BlackRock rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI Agents

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG and AI Agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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