Private Equity Senior Data Engineer
About Valor
Valor Real Estate is a last-mile logistics real estate private equity manager with c.€5bn AUM across more than 200 buildings and significant capital available for further investment. Valor has c.€1bn available funding raised as dry powder for investment with a large institutional investor.
About Research and Technology
Our Research & Technology team works closely with our private equity partners, operating as an extension of their deal teams to develop investment theses, identify structural trends and evaluate opportunities across EMEA.
We combine market research with modern data infrastructure and analytics to deliver actionable insights that support underwriting, portfolio strategy and capital allocation decisions. By leveraging automation, scalable cloud systems and advanced data engineering, we transform fragmented real estate and market data into structured intelligence.
We are hiring a Senior Data Engineer to take ownership of our data platform. You will work directly with the Head of Research and across the investment, asset management, and finance teams to build the systems that underpin Valor's investment process.
Responsibilities:
- Own end-to-end data platform architecture — ingestion, storage, modelling, and consumption layers
- Define and enforce data governance standards — lineage tracking, access controls, and quality frameworks
- Convert existing Excel-based financial and research models into maintainable, tested Python logic, preserving and formalising embedded business rules
- Build reusable analytical libraries covering real estate metrics and investment KPIs
- Build and maintain CI/CD pipelines, scheduling infrastructure, and a control dashboard for pipeline observability
- Drive efficiency through automation across research, investment, finance, and asset management
- Design and deploy agent-based and multi-agent AI workflows to support the research and investment process
- Lead delivery of new technology initiatives end-to-end, from scoping through to production
- Work directly with non-technical stakeholders to translate business needs into technical solutions
What We're Looking For:
- Candidates with analytical and numerical backgrounds, with relevant Degrees in Engineering, computer science, maths related fields
- 5+ years of hands-on data engineering experience, with time in a small team where you have owned systems end-to-end
- Strong Python and SQL
- Deep experience with Snowflake (or equivalent cloud warehouse), dbt, and modern orchestration tools (Airflow, Dagster, Prefect), and Docker
- Demonstrable track record of designing and operating production ETL/ELT pipelines from ambiguous source data through to clean, governed consumption layers
- Practical experience building CI/CD pipelines and observability tooling for data systems
This is a fast-paced environment where priorities evolve and engineers are expected to adapt accordingly. The role is hands-on and full-stack, working in close partnership with the business.
Equal Opportunities
We are an equal opportunities employer and are committed to creating an inclusive environment for all employees. We welcome applications from all suitably qualified individuals regardless of age, disability, gender identity or expression, race, religion or belief, sex, sexual orientation, marital status, pregnancy or maternity. All employment decisions are made based on merit, skills and business need.