We are looking for a data-savvy Software Engineer to help us build scalable, production-grade systems for researching, experimenting and developing cutting-edge data products in the private markets space.
This role sits within the Private Markets Data Engineering (PMDE) team at Preqin, part of BlackRock. Preqin is central to BlackRock’s ambition to transform private markets data and technology, complementing the Aladdin platform to deliver integrated public and private market solutions across the whole portfolio.
As a senior individual contributor and hands-on technical leader, you will design and build scalable data software infrastructure and analytics platforms that enable high-quality data products, advanced analytics, and client-facing solutions. Working closely with business stakeholders and product partners, you will translate strategic priorities and user needs into robust technical architectures and delivery plans. You will operate with a high degree of autonomy, owning technical design and outcomes across complex initiatives.
Your work will directly enhance transparency, operational efficiency, and data-driven decision-making for institutional investors, fund managers, and service providers. In doing so, you will help position BlackRock as the leading technology and data provider in private markets.
This role is ideal for someone who is excited by the challenges of innovating in private markets data, and combines deep technical expertise with the ability to clearly articulate value to both business stakeholders and clients.
Key responsibilities:
Architect and build scalable, reliable data pipelines and platformssoftware solutions for data products, ensuring performance, quality, and long-term sustainability.
Own data solutions end-to-end — from translating business objectives into technical designs through implementation, deployment, and production support.
Design and implement data workflows that are reproducible, testable, and scientifically rigorous, embedding validation frameworks, monitoring, lineage, and observability into every stage.
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Enable advanced analytics and AI/ML use cases by building software solutions infrastructure that supports experimentation, versioning, and production-grade pipeline and model deployment.
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 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.
What we are looking for:
Proven experience building and operating scalable software systems for data processing workflows and platforms, with deep expertise in Python and SQL across databases such as Snowflake and Postgres.
Hands-on experience with modern software engineering practices, including version control (Git), CI/CD pipelines, automated testing frameworks, and containerisation and orchestration (Docker, Kubernetes).
Experience working in cloud environments (AWS or Azure), including infrastructure provisioning and automation using Infrastructure as Code (e.g., Terraform).
Demonstrated ability to design production-grade systems that balance performance, scalability, reliability, security, and maintainability.
Experience enabling or supporting advanced analytics and AI/ML use cases in production environments.
A rigorous, data-driven mindset – comfortable using analysis, benchmarking, and experimentation to guide technical decisions and architectural trade-offs.
Strong understanding of data validation, testing strategies, and code quality practices, with confidence applying diverse code and data testing techniques across data and application layers.
Ability to operate autonomously and drive technical solution design end-to-end, taking ownership of outcomes.
Experience collaborating effectively across engineering, data science, product, and design teams to deliver high-impact solutions.
Excellent written and verbal communication skills, with the ability to influence stakeholders at all levels and translate complex technical concepts into clear, business-relevant language.
A proactive, curious, and resilient mindset — motivated to explore new technologies, tackle ambiguous problems, and continuously improve systems and ways of working.
Desirable skills include:
Experience with AI-related technologies and products; familiarity with using AI coding assistants.
Experience working with financial market data, investment analytics, or private markets datasets.
Experience designing and building data platformssoftware and/or data platforms in regulated or financial services environments.
Experience supporting ML lifecycle management (model versioning, experiment tracking, model deployment pipelines); familiarity with tools such as MLflow, feature stores, or model serving frameworks.
Experience productionising statistical or quantitative models.
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.
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