Vice President, Software Engineer (Private Markets Data)
BlackRock · London, Greater London ·
- Work mode
- Hybrid
- Seniority
- C level
- Category
- Software engineering
- Visa sponsorship
- Yes
- Company size
- 1000+
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Build and lead scalable data systems for private markets analytics at BlackRock, combining hands-on engineering with team leadership to deliver AI/ML-driven insights for institutional investors.
About this role
Your team
This role sits within Preqin, part of BlackRock, and is aligned to the Derived Data team. Preqin is a leading provider of private markets data and analytics, delivering trusted data, benchmarks, and insights that support decision-making across the private markets investment lifecycle. The team develops high-quality data products and scalable technology solutions that increase transparency and enable data-driven decision-making across private markets. Your work will contribute directly to BlackRock’s strategy of delivering integrated public and private market solutions.
Your role and impact
We are looking for a data-savvy software engineer to help build scalable, production-grade systems that support the research, experimentation, and development of innovative private markets data products. As a Vice President, you will operate in a player-coach model, combining hands-on technical leadership with people management responsibilities. You will partner closely with product, analytics, and business stakeholders to translate strategic priorities into robust technical solutions and delivery plans while setting a high bar for engineering excellence, reliability, and operational maturity. Your work will enhance transparency, operational efficiency, and data-driven decision-making for institutional investors and private markets clients, helping position BlackRock as a leading technology and data provider in private markets.
Key responsibilities:
Architect, build, and own scalable software solutions end-to-end, translating business objectives into technical designs through implementation, deployment, and production support.
Design and implement reproducible, testable data workflows that enable advanced analytics and Artificial Intelligence and Machine Learning (AI/ML) use cases, incorporating validation, monitoring, observability, experimentation, versioning, and production deployment capabilities.
Lead architectural decisions and influence technical prioritisation, partnering closely with product and delivery teams to align engineering effort with business impact.
Act as a technical authority within the wider team, elevating engineering standards and driving best practices in data management, governance, and cloud-native development.
Engage senior stakeholders, clearly communicating complex technical trade-offs and recommendations in business-relevant terms.
Collaborate cross-functionally with engineers, data scientists, analysts, and product leaders to deliver high-impact solutions for institutional investors and private markets clients.
Lead, coach, and develop software engineers, combining hands-on technical contribution with people management to foster a high performing, inclusive, and continuously improving engineering culture.
What we are looking for:
Demonstrated ability to design, build, and operate scalable production-grade software systems for data processing, including expertise in Python, SQL, and modern data platforms.
Hands-on experience with modern software engineering practices and tooling, including version control, CI/CD, automated testing frameworks, containerisation, and AI-augmented software development workflows.
Experience working in cloud environments such as Amazon Web Services (AWS) or Microsoft Azure, including infrastructure provisioning and automation using Infrastructure as Code.
Strong understanding of data validation, testing strategies, code quality practices, and the ability to independently drive technical solutions from design through delivery.
Experience supporting advanced analytics and AI/ML use cases, complemented by a rigorous, data-driven approach to experimentation, evaluation, and technical decision-making.
Excellent collaboration, communication, and stakeholder management skills, with the ability to influence across engineering, product, data science, and business teams.
A proactive, curious, and resilient mindset, with a demonstrated ability to navigate ambiguity, explore new technologies, and continuously improve systems and ways of working.
Experience leading, mentoring, and developing software engineers while maintaining hands-on technical credibility.
Desirable skills include:
Experience working with financial market data, investment analytics, or private markets datasets.
Experience designing and building software and/or data platforms in financial services environments or other regulated environments.
Experience productionising statistical or quantitative models.
Experience supporting AI/ML lifecycle management, including model versioning, experiment tracking, evaluation, serving and deployment pipelines.
Our benefits
To help you stay energized, engaged and inspired, we offer a wide range of employee benefits including: retirement investment and tools designed to help you in building a sound financial future; access to education reimbursement; comprehensive resources to support your physical health and emotional well-being; family support programs; 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, race, religion, sex, sexual orientation and other protected characteristics at law.
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