Senior Data Platform Engineer (Python & Databricks)

Job summary

Codelitt is seeking a Senior Data Platform Engineer to develop and maintain a financial data platform using Databricks and Python. The role involves building data pipelines, designing data models, and collaborating with a hybrid engineering team in Edinburgh.

Qualifications

• Five or more years of professional software-engineering experience
• Strong experience developing production applications with Python
• Hands-on experience building production workloads with Databricks
• Experience designing and maintaining data pipelines
• Strong understanding of data modeling and data-processing concepts
• Experience designing or consuming APIs in distributed systems
• Experience working with relational databases and SQL
• Strong automated-testing and software-quality practices
• Experience with version control, code review, and CI/CD workflows
• Ability to understand and contribute to an established, complex codebase
• Strong written and verbal English communication skills
• Ability to work independently while collaborating closely with a broader engineering team
• Ability to attend the Edinburgh office regularly, typically one to two days per week

Responsibilities

• Build and maintain components of a large-scale financial data platform
• Develop reliable data pipelines for ingesting, transforming, and delivering financial data
• Design data models that support enterprise reporting, analytics, and downstream integrations
• Improve performance, reliability, maintainability, and observability of existing data workflows
• Troubleshoot complex issues across data-processing and application layers
• Design, build, and maintain production-grade applications and services using Python
• Develop well-structured APIs for accessing and managing data-platform capabilities
• Write clean, testable, maintainable, and well-documented code
• Participate in architectural and technical-design discussions
• Review code and help maintain high engineering standards across the team
• Build and operate production workloads using Databricks
• Help improve organization and execution of Databricks-based data workflows
• Work with large datasets and complex transformation requirements
• Apply Databricks best practices to improve scalability, reliability, and developer productivity
• Collaborate with a hybrid engineering team based in Edinburgh
• Communicate progress, risks, dependencies, and blockers proactively
• Take ownership of assigned initiatives from technical discovery through delivery
• Contribute to documentation and internal knowledge sharing

Skills

Relocation