Codelitt
Senior Data Platform Engineer (Python & Databricks)

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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. Here you'll find our office location. 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.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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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.


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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.
Please note: We are not currently interested in working with external recruiters or staffing agencies.
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