Databricks Architect

Technology – Databricks (Spark, PySpark/SQL) and data lake architectures

Location – London, UK

Duration-Permanent

We are looking for a Data Architect to design, build, and operate scalable data pipelines and data products, enabling a modern data mesh architecture. The role focuses on integrating legacy systems with cloud-native platforms to support analytics, reporting, and domain-owned data products.

• Strong experience with Databricks (Spark, PySpark/SQL) and data lake architectures.
• Hands‑on experience with streaming technologies, especially Kafka / Confluent Kafka.
• Experience integrating legacy data sources such as DB2 (mainframe) and SQL Server.
• Working knowledge of AWS data services, especially S3.
• Understanding of data product thinking, data mesh concepts, and modern data engineering best practices.

• Build and maintain batch and streaming data pipelines from legacy mainframe DB2 and on prem SQL Server systems into an AWS-based data lake.
• Implement real‑time ingestion using Confluent Kafka and land data in Amazon S3.
• Develop data transformations and analytics pipelines in Databricks using the medallion architecture (Bronze, Silver, Gold).
• Design and deliver high‑quality, reusable data products aligned to data mesh principles.
• Ensure data quality, reliability, security, and governance across pipelines.
• Collaborate with domain teams, platform teams, and stakeholders to enable self‑serve analytics and consumption.

• Experience in banking or financial services data platforms.
• Familiarity with data governance, metadata management, and regulatory reporting