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Databricks Data Engineer | Real Estate Investment - Contract

Marks Sattin Ltd London, United Kingdom
Posted 1 day ago Contract £600 - £700 per day

Databricks Data Engineer | Real Estate Investment - Contract

Marks Sattin Ltd London, United Kingdom
Databricks Data Engineer | Real Estate Investment - Contract
Senior Databricks Data Engineer | Global Real Estate Investment Manager | London (Hybrid)

Marks Sattin is partnering with a global real estate investment and asset management organisation undergoing a significant transformation of its data estate. As part of a wider modernisation programme, the business is migrating critical real estate data capabilities from legacy SQL Server environments into a modern Databricks platform, creating a more scalable, governed and future-ready foundation for analytics, reporting and investment decision-making.

This is an opportunity to play a key role in shaping the future of a business-critical data platform used across real estate equity and debt operations. Working within the Real Estate Technology team, you'll collaborate with business, finance and technology stakeholders to modernise data models, rationalise legacy processes and establish best-practice data engineering standards that will support the organisation for years to come.

You'll join a highly visible programme where your work will directly influence platform architecture, data governance and reporting capabilities across a complex investment environment.

What You'll Do
  • Lead the assessment and modernisation of legacy SQL Server, ETL and reporting workloads into a Databricks-based architecture.
  • Design scalable data models, Delta Lake structures and transformation pipelines supporting real estate investment data.
  • Analyse data lineage, dependencies, business logic and data quality to determine what should be migrated, redesigned or retired.
  • Build robust reconciliation, monitoring and governance controls to ensure accuracy, auditability and operational resilience.
  • Partner closely with investment, finance and technology teams to deliver a phased migration strategy aligned to business objectives.

What You'll Bring
  • Strong experience with SQL Server, T-SQL, Databricks and Spark SQL in enterprise environments.
  • Proven track record delivering large-scale data migration or modernisation programmes.
  • Expertise in relational, dimensional and analytical data modelling, including modern lakehouse and medallion architectures.
  • Experience performing data profiling, lineage analysis, source-to-target mapping and data quality assessment.
  • Strong understanding of production-grade data platforms, performance optimisation and operational support.
  • Experience migrating SSIS, ETL pipelines, stored procedures and reporting solutions to cloud-based platforms.
  • Exposure to Azure DevOps, Git and CI/CD practices.
  • Experience with Python, PySpark, Power BI or real estate technology platforms would be advantageous.
  • Previous exposure to commercial real estate, investment management or alternative asset management environments is highly desirable.

This role will suit a senior data professional who enjoys solving complex platform challenges and influencing strategic technology decisions rather than simply maintaining existing systems. You'll have the opportunity to shape the target-state architecture, establish best practices and leave a lasting impact on a critical transformation programme within a globally recognised investment business.

If you're interested in helping build the next generation of real estate data capabilities, we'd love to hear from you. Please get in touch or share your CV for a confidential discussion.

We are happy to provide application and/or accessibility support, please contact your Marks Sattin or Grafton consultant directly to discuss your needs. We're committed to protecting the privacy of all our candidates and clients, please visit https://www.markssattin.co.uk/privacy and https://uk.grafton-recruitment.com/en/privacy-policy-1 for our privacy policy.
Job ID  BBBH194656
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