Data Integration Lead (Databricks & Salesforce)

Overview

Job Title: Data Integration Lead (Databricks & Salesforce)

Salary: £115,000 - £130,000 + 20% Bonus

Company: Confidential Financial Services Firm

About the Role

A leading financial services organisation is seeking a Data Integration Lead to drive the next phase of its data platform evolution, with a focus on integration and optimisation.

With Databricks now largely established and legacy pipelines approaching consolidation, the priority has shifted toward connecting the data platform with core business systems, particularly Salesforce.

This is a high-impact, cross-functional role positioned between a well-established Databricks team and a high-performing Salesforce function, with a clear mandate to design and own the integration layer between the two.

You will report directly to the Head of Salesforce, acting as the key technical bridge between data and CRM.

Key Responsibilities

• Design and implement scalable integrations between Databricks and Salesforce
• Enable seamless data flow between the data platform and business systems
• Support the final consolidation phase of legacy ADF pipelines, ensuring clean integration into the target architecture
• Develop and maintain reliable, well-governed data interfaces and APIs
• Collaborate closely with Data Engineering and Salesforce teams to align on data models and integration patterns
• Improve data accessibility and usability for downstream business processes
• Monitor and optimise integration performance, reliability, and cost
• Act as the subject matter expert for cross-platform integration

Required Skills & Experience

• Strong background in data engineering or data integration
• Hands-on experience with Databricks (Spark, Delta Lake)
• Experience working with Azure Data Factory (ADF) in production environments
• Proven experience integrating with Salesforce (APIs, data models, data sync patterns)
• Strong SQL and Python skills
• Experience designing robust ETL/ELT and integration workflows
• Solid understanding of data architecture and system integration patterns

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