Director - Hyperion Engineering

About this role

About Hyperion

Hyperion is BlackRock's strategic platform for AI-enabled processing of unstructured data, in particular related to Private Markets. The platform enables internal and eventually external customers to build data processing workflows.

The goal is to automatically process millions of documents, news articles, and websites every day by leveraging the latest technology for workflow orchestrations and AI data processing.

Role Overview

You will join BlackRock's Private Markets Data Engineering organisation, leading the development of the Hyperion platform.

You will lead the team that designs, builds, and operates a scalable, production-grade platform in close alignment with other leaders of the project as well as leaders of other areas of BlackRock.

Key Responsibilities

• Own senior technical leadership and architectural direction for the nascent Hyperion platform, i.e., making strategic trade-offs, solve complex challenges, and adopt innovative technologies, in close collaboration with other leaders.

• Enhance our culture, centred around empowering each team member to innovate and instilling a strong sense of ownership.

• Collaborate with leaders of BlackRock Aladdin to define the strategic direction and priorities of the project.

• Lead, coach, and develop engineers, combining hands-on technical contribution with people management.

• Own the end-to-end delivery of this complex, business critical platform, from design through sustained production operation, with accountability for outcomes, reliability, and trust.

• Build strong relationships with other internal platform teams, to co-design the overall architecture and partner towards a common goal.

• Design the platform in a way that enables early adopters while driving towards a self-service approach for developers and non-technical users.

• Demonstrated experience (10+ years) designing and launching enterprise scale, production grade platforms, with a strong track record of reliability, performance, and stakeholder trust in business-critical environments.

• Proven ability to exercise senior technical judgement, making architectural and prioritisation trade-offs across complex data ecosystems, including scalability, cost, governance, and long-term sustainability considerations.

• Advanced expertise distributed systems and workflow orchestration.

• Proficiency in Python for building and operating data pipelines, orchestration, and automation, supported by solid software engineering fundamentals (version control, testing, CI/CD).

• Advanced expertise with modern platform infrastructure and enablement practices, including infrastructure-as-code (Terraform or equivalent), container orchestration (Kubernetes), and related cloud-native technologies.

• Experience leading, mentoring, and developing engineers while building a strong team culture with a strong sense of ownership and proactive innovation.

• Exposure to AI enabled capabilities for processing of unstructured data.

• Experience in financial markets.

• You operate with a strong sense of ownership and accountability, taking responsibility for complex, business critical data platforms and driving initiatives through to sustained production impact.

• You continuously strive to improve culture beyond your team.

• You apply rigorous, analytical thinking to ambiguous problems, using evidence, engineering judgement, and structured decision-making to deliver scalable, well governed solutions.

• You set a high bar for engineering excellence, embedding best practices in security, code quality, documentation, testing, and operational resilience.

• You collaborate effectively across disciplines, building trusted partnerships with product, analytics, and business stakeholders.

• You lead through influence and example, fostering an inclusive, collaborative, and high performing engineering culture.

• You demonstrate a growth mindset and continuous improvement orientation, embracing change and challenging established ways of working to deliver better outcomes at scale.