Vice President, Software Engineer (Private Markets Data)

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.