Data Engineer, Vice President

Preqin is a leading provider of private markets data and analytics and part of BlackRock. It delivers trusted data benchmarks and insights that support decisionmaking across the full private markets investment lifecycle.

With comprehensive global coverage across private equity private credit real estate infrastructure venture capital and hedge funds Preqin brings greater transparency to private markets through rigorous data collection deep market expertise and continuously evolving methodologies. Its data and technology underpin how investors raise capital evaluate opportunities monitor portfolios and assess performance at scale.

About Company Intelligence

Company Intelligence is Preqins private company data platform providing structured auditable companylevel data and analytics across the private markets investment lifecycle. It integrates company deal and ownership data with fund manager and performance information to deliver a connected view of private capital activity.

Built on granular data and robust methodologies Company Intelligence supports scalable analysis across deal sourcing due diligence valuation benchmarking and comparative research. By increasing transparency across the private company universe it provides a connected view of company activity within the broader private capital ecosystem.

Role Overview

You will join BlackRocks Private Markets Data Engineering organisation working on Preqins Company Intelligence platform at the core of our private markets data this role you will design build and operate scalable productiongrade data platforms and pipelines that underpin the expansion of Preqins global private company universe enabling broader coverage deeper data and more advanced analytics.

As a Vice President you will operate as a playercoach: a senior individual contributor providing handson technical leadership while also managing and developing a small team of data engineers. You will own complex data engineering initiatives endtoend partner closely with product analytics and business stakeholders and set a high bar for engineering excellence reliability and operational maturity in an enterprise environment.

Key Responsibilities

• Provide senior technical leadership and architectural direction for data platforms and pipelines that enable the scalable expansion of Preqins private company universe ensuring performance cost efficiency and longterm maintainability.
• Own the endtoend delivery of complex businesscritical data engineering initiatives from design through sustained production operation with accountability for outcomes reliability and data trust.
• Drive a platformcentric data engineering strategy building reusable frameworks shared datasets and extensible pipelines that support multiple Company Intelligence products and advanced analytics use cases.
• Ensure high standards of data quality governance lineage and observability proactively managing operational and compliance risks across enterprisegrade data products.
• Partner effectively with product analytics and business leaders developing a deep understanding of strategic objectives and translating them into data platforms that deliver measurable business value.
• Lead coach and develop data engineers combining handson technical contribution with people management to foster a highperforming inclusive and continuously improving engineering culture.

Required Experience

• Demonstrated experience (5 years) operating enterprisescale productiongrade data platforms with a strong track record of reliability performance and stakeholder trust in businesscritical environments.
• Proven ability to exercise senior technical judgement making architectural and prioritisation tradeoffs across complex data ecosystems including scalability cost governance and longterm sustainability considerations.
• Advanced expertise in SQL and analytical data modelling with sustained experience building highquality wellgoverned datasets used broadly across analytics research and decisionmaking functions.
• Strong background in modern analytics engineering including dbtbased transformation layers testing strategies documentation and embedded data quality practices in production environments.
• Proficiency in Python for building and operating data pipelines orchestration and automation supported by solid software engineering fundamentals (version control testing CI/CD).
• Experience building and operating data pipelines using workflow orchestration frameworks (e.g. Apache Airflow) with a focus on reliability observability dependency management and operational resilience.
• Experience designing and operating cloudnative data platforms (AWS or Azure preferred) and enterprise data warehouses (Snowflake preferred) including performance tuning cost controls and secure access patterns.
• Experience leading mentoring and developing data engineers while maintaining handson technical credibility.
  

Desirable Experience

• Experience working with private markets or alternative investment data (e.g. private equity private credit real assets venture capital) supporting investment research or portfoliolevel analytics at scale.
• Exposure to advanced analytics or AIenabled capabilities embedded within data platforms such as automation modeldriven data products or AIassisted workflows.
• Familiarity with modern data platform infrastructure and enablement practices including infrastructure as code (Terraform or equivalent) container orchestration (Kubernetes) and related cloudnative technologies.

Who You Are

• You operate with a strong sense of ownership and accountability taking responsibility for complex businesscritical data platforms and driving initiatives through to sustained production impact.
• You apply rigorous analytical thinking to ambiguous problems using evidence engineering judgement and structured decisionmaking to deliver scalable wellgoverned 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 highperforming 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.