At a Glance
- Tasks: Build and maintain a cutting-edge financial data platform using Python and Databricks.
- Company: Join Codelitt, a dynamic team of innovators solving complex tech challenges.
- Benefits: Enjoy generous paid time off, sick leave, and parental leave.
- Other info: Hybrid role with opportunities for career growth and team-building activities.
- Why this job: Make a real impact in the finance sector while collaborating with global experts.
- Qualifications: 5+ years in software engineering, strong Python and Databricks skills required.
The predicted salary is between 63000 - 77000 £ per year.
About Codelitt
At Codelitt, we are more than a product-development company. We are creators, innovators, and problem solvers. We partner with companies around the world to design and build meaningful digital products, modernize complex systems, and solve challenging technical problems. Our globally distributed team values technical excellence, ownership, proactive communication, and collaboration.
About the Role
We are looking for a Senior Data Platform Engineer to join a high-impact engagement with one of our partners, a global leader in wealth-management technology. This is a hybrid position to work in our office in Edinburgh. We expect the engineer working in this position to go to the office between 1 to 2 times per week.
You will help build and evolve a financial data platform developed on top of Databricks and used by major enterprise clients. The platform supports the ingestion, transformation, modeling, and delivery of complex financial data. This is primarily a backend and data-platform position. You will work across Python services, APIs, data pipelines, and data models while collaborating closely with an established engineering team in Edinburgh.
The ideal candidate has substantial hands-on Databricks experience and can become productive in a complex data environment. You should be comfortable taking ownership of well-defined areas of work while gradually building a broader understanding of the platform.
What You’ll Do
- Data Platform Development
- 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 the performance, reliability, maintainability, and observability of existing data workflows.
- Troubleshoot complex issues across data-processing and application layers.
- Python and API Development
- 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 a high engineering standard across the team.
- Databricks Engineering
- Build and operate production workloads using Databricks.
- Help improve the 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.
- Collaboration and Ownership
- Work directly with engineers and technical leaders from both Codelitt and our partner.
- Collaborate with a hybrid engineering team based in Edinburgh.
- Break complex requirements into clear and manageable technical tasks.
- Communicate progress, risks, dependencies, and blockers proactively.
- Take ownership of assigned initiatives from technical discovery through delivery.
- Contribute to documentation and internal knowledge sharing.
Required Qualifications
- Five or more years of professional software-engineering experience.
- Strong professional 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 working 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.
Preferred Qualifications
- Experience building data platforms for financial-services or other data-intensive industries.
- Experience with cloud-based data architectures.
- Familiarity with infrastructure-as-code tools such as Terraform.
- Experience improving the observability and operational reliability of data pipelines.
- Familiarity with modern data governance, access-control, and data-quality practices.
- Experience working in an enterprise environment with strict security and compliance requirements.
- Front-end experience with React or another modern JavaScript framework.
- Front-end development and infrastructure work may occasionally be required, but they are not the primary focus of this position. Deep Kubernetes expertise is not required.
Who You Are
- Databricks Experienced: You have used Databricks in a real production environment and understand how to build, maintain, and troubleshoot data workloads on the platform.
- Python Focused: You can design and implement reliable Python services and APIs, not simply scripts or notebooks.
- Data Oriented: You understand how data moves through a platform and can reason about ingestion, transformation, modeling, quality, performance, and downstream consumption.
- Proactive: You communicate before a problem becomes a surprise. When blocked, you raise the issue, explain its impact, and help identify a path forward.
- Comfortable with Complexity: You can navigate a mature platform with significant internal context. You know how to ask effective questions, document what you learn, and gradually expand your ownership.
- Collaborative: You enjoy working with other engineers, sharing knowledge, reviewing designs, and contributing to a healthy engineering culture.
What We Offer
- Generous paid-time-off policy.
- Paid sick leave.
- Paid parental leave.
- Opportunities to work on challenging products with experienced international teams.
- A collaborative environment that values technical quality and personal ownership.
- Regular team-building activities throughout the year.
Codelitt is a close-knit global team that moves quickly, communicates openly, and enjoys solving difficult problems together. If you are an experienced Python engineer with strong Databricks knowledge and an interest in building enterprise data platforms, we would love to hear from you.
Senior Data Platform Engineer (Python & Databricks) employer: Codelitt
Codelitt is an exceptional employer that fosters a collaborative and innovative work culture, where technical excellence and personal ownership are highly valued. Located in the vibrant city of Edinburgh, our hybrid work model allows for flexibility while still encouraging team interaction through regular office visits. Employees benefit from generous paid time off, opportunities for professional growth, and the chance to work on challenging projects with a diverse international team.
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We think this is how you could land Senior Data Platform Engineer (Python & Databricks)
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We think you need these skills to ace Senior Data Platform Engineer (Python & Databricks)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
