Live opening · Posted 7 days ago

VP - Senior Data Engineer

BlackRock · Bengaluru, India
Workday
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At a glance

The key details from the original listing.

Posted 7 days ago
CompanyBlackRock
LocationBengaluru, India
SourceWorkday
Listed7 days ago

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About the role

Description supplied by the original job listing.

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

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