Data engineer in private markets

Company Intelligence is Preqin's private company data platform, providing structured, auditable company-level data and analytics across the private markets investment lifecycle. The platform 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 rigorous methodologies, Company Intelligence enables scalable analysis across deal sourcing, due diligence, valuation benchmarking, and comparative research.

• Provide senior technical leadership and architectural direction for data platforms and pipelines that support the scalable expansion of Preqin's private company universe while ensuring performance, cost efficiency, and maintainability.
• Own the end-to-end delivery of complex, business-critical data engineering initiatives, from solution design through production operation, with accountability for reliability, quality, and business outcomes.
• Drive a platform-centric engineering strategy by developing reusable frameworks, shared datasets, and extensible data products that support multiple Company Intelligence use cases.
• Establish and maintain high standards for data quality, governance, lineage, observability, and operational risk management across enterprise-grade data assets.
• Partner with product, analytics, and business stakeholders to translate strategic objectives into scalable data solutions that deliver measurable business value.
• Lead, coach, and develop a team of data engineers while maintaining hands-on technical contribution and fostering a collaborative, high-performing engineering culture.

• Demonstrated experience designing, building, and operating enterprise-scale data platforms, applying sound architectural judgement across scalability, governance, cost efficiency, reliability, and long-term sustainability.
• Advanced expertise in SQL, analytical data modelling, and modern analytics engineering practices, including transformation frameworks, testing, documentation, and embedded data quality controls.
• Strong proficiency in Python and data pipeline engineering, including orchestration, automation, dependency management, observability, and operational resilience in production environments.
• Experience designing and operating cloud-native data platforms and enterprise data warehouses, supported by modern platform engineering practices such as infrastructure as code and container orchestration.
• Experience leading, mentoring, and developing data engineers while maintaining strong hands-on technical credibility.
• Experience working with private markets or alternative investment data, supporting investment, research, or portfolio analytics at scale.
• Exposure to advanced analytics and artificial intelligence-enabled capabilities, including automation, model-driven data products, and intelligent workflow solutions.

• 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
• Flexible Time Off (FTO) so you can relax, recharge and be there for the people you care about.
• 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.