Python Data Engineer
About the role
Monachil’s investment process runs on data — loan-level performance, collateral positions, and reconciled portfolio views delivered daily to our investment team. We’re looking for a hands-on Python Data Engineer to help design, build, and harden the pipelines and services that keep this platform correct, timely, and observable.
You’ll work in an Azure environment and play a meaningful part in our evolution from a monolithic application toward a service-oriented architecture. The role is deeply technical and calls for strong computer-science fundamentals, careful attention to detail, and a commitment to clean, well-documented code.
Key responsibilities
- Build and maintain Python-based ETL and data pipelines that ingest, transform, and validate daily batch datasets from originator source systems.
- Work with blob and object storage systems, and understand the trade-offs between columnar and row-based formats (e.g. Parquet, Avro).
- Apply data-validation frameworks (Pydantic, Pandera, or similar) to enforce schema correctness and data integrity end to end.
- Design schemas and interact with relational databases (SQLAlchemy or equivalent ORM) as well as NoSQL / document stores via ODM patterns.
- Implement FastAPI-based services that expose data and analytics to internal consumers, laying the groundwork for a microservices architecture.
- Refactor existing code to improve readability, reliability, and test coverage; reduce technical debt through structured design, strong logging, and good test hygiene.
- Apply MapReduce and distributed-processing concepts to prepare pipelines for scale.
- Document pipelines, schemas, APIs, and processes clearly and keep that documentation current as part of the definition of done.
- Collaborate across teams to translate investment and operations requirements into robust technical solutions.
- Stay adaptable in an environment where priorities evolve quickly.
Qualifications
- Approximately 2–3 years of relevant experience, or equivalent demonstrated capability.
- Strong Python skills, including Pandas, for data manipulation and pipeline development.
- Working knowledge of blob / object storage and columnar / row-based data formats.
- Familiarity with data-validation frameworks and schema enforcement.
- Proficiency with SQL and relational databases using ORM patterns, plus exposure to NoSQL / document models via ODM.
- Experience with FastAPI, RESTful API design, and structured code practices.
- Solid grounding in algorithms, data structures, and software-engineering fundamentals.
- Strong habits around logging, testing, and documentation.
- Awareness of CI/CD concepts; cloud-environment familiarity (Azure is a plus).
Nice to have
- Familiarity with orchestration tools (Airflow, Prefect) or distributed frameworks (Spark, Databricks).
- Hands-on exposure to Azure Data Factory, Synapse, or similar services.
- Prior work at a fintech, asset manager, or other data-intensive financial firm.
How to apply
Submit the form on this page with your resume and a short note on what draws you to this role. We read every application.