Senior Data Platform Engineer (Python & Databricks)

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.

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 remote position from Latam.

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 New York.

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.

We process our payment in US dollars, however you can receive it in your local currency.

• 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.

• 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.

• 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.

• Work directly with engineers and technical leaders from both Codelitt and our partner.

• Collaborate with a hybrid engineering team based in New York.

• 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.

• 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.

• 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.

You have used Databricks in a real production environment and understand how to build, maintain, and troubleshoot data workloads on the platform.

You can design and implement reliable Python services and APIs, not simply scripts or notebooks.

You understand how data moves through a platform and can reason about ingestion, transformation, modeling, quality, performance, and downstream consumption.

You communicate before a problem becomes a surprise. When blocked, you raise the issue, explain its impact, and help identify a path forward.

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.

You enjoy working with other engineers, sharing knowledge, reviewing designs, and contributing to a healthy engineering culture.