Data Engineer, Vice President

Salary: £61,000 - 101,000 per year

Requirements:

• At least 5 years of experience operating enterprise-scale, production-grade data platforms, with a strong track record of reliability, performance, and stakeholder trust in business-critical environments.
• Proven ability to exercise senior technical judgment and make architectural and prioritization trade-offs across complex data ecosystems, including scalability, cost, governance, and long-term sustainability.
• Advanced expertise in SQL and analytical data modeling, with experience building high-quality, well-governed datasets used across analytics, research, and decision-making.
• Strong background in modern analytics engineering, including dbt-based transformation layers, testing strategies, documentation, and production data quality practices.
• Proficiency in Python for building and operating data pipelines, orchestration, and automation, supported by software engineering fundamentals such as version control, testing, and CI/CD.
• Experience with workflow orchestration frameworks such as Apache Airflow, focusing on reliability, observability, dependency management, and operational resilience.
• Experience designing and operating cloud-native 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 hands-on technical credibility.
• Desirable: Experience with private markets or alternative investment data, supporting investment, research, or portfolio-level analytics at scale.
• Desirable: Exposure to advanced analytics or AI-enabled capabilities embedded in data platforms, such as automation, model-driven data products, or AI-assisted workflows.
• Desirable: Familiarity with infrastructure as code (Terraform or equivalent), container orchestration (Kubernetes), and related cloud-native technologies.
• Strong ownership and accountability, analytical thinking, sound engineering judgment, and a commitment to engineering excellence, collaboration, inclusion, and continuous improvement.

Responsibilities:

• Provide senior technical leadership and architectural direction for data platforms and pipelines that enable the scalable expansion of our global private company universe, ensuring performance, cost efficiency, and long-term maintainability.
• Own complex, business-critical data engineering initiatives end-to-end, from design through sustained production operation, with accountability for outcomes, reliability, and data trust.
• Drive a platform-centric data engineering strategy by building reusable frameworks, shared datasets, and extensible pipelines for multiple Company Intelligence products and advanced analytics use cases.
• Ensure high standards of data quality, governance, lineage, and observability, and proactively manage operational and compliance risks across enterprise-grade data products.
• Partner with product, analytics, and business leaders to understand strategic objectives and translate them into data platforms that deliver measurable business value.
• Lead, coach, and develop data engineers, combining hands-on technical contribution with people management to foster a high-performing, inclusive, and continuously improving engineering culture.

Technologies:

• AI
• Airflow
• AWS
• Azure
• CI/CD
• Cloud
• Embedded
• Support
• Kubernetes
• Python
• SQL
• Snowflake
• Terraform
• dbt
• Security

More:

We are a global investment management firm focused on helping more people experience financial well-being. Our private markets data business provides data, benchmarks, and insights across private equity, private credit, real estate, infrastructure, venture capital, and hedge funds. Company Intelligence is our private company data platform, connecting company, deal, ownership, fund, manager, and performance information to support analysis across the private markets investment lifecycle. In this Vice President role, you will join our Private Markets Data Engineering organization as a player-coach, providing hands-on technical leadership while managing a small team. We offer retirement investment resources, education reimbursement, physical and emotional well-being resources, family support programs, and Flexible Time Off. Our hybrid model currently requires employees to work in the office at least four days a week, with one day of work-from-home flexibility; some groups may require more office time. We encourage candidates to use AI thoughtfully to prepare, while interviews focus on candidates own experience, thinking, and judgment. We are an equal opportunity employer and evaluate qualified applicants without regard to protected characteristics under applicable law.

last updated 40 week of 2026