Analytics Engineer

We are looking for a Python Developer to build and maintain the next-generation analytics platform supporting performance attribution, portfolio risk, and alternative investments . You will collaborate closely with investment analysts and data engineers to deliver scalable data pipelines, analytics services, and intuitive dashboards.

Key Responsibilities

Back-End Development

Design, code, and optimize Python applications for performance attribution, portfolio analytics, and risk modeling. Develop APIs and microservices to integrate data from multiple sources (market data, alternative assets, digital investment feeds).

Data Engineering & Cloud

Build ETL pipelines to ingest and transform large datasets using AWS S3 and Snowflake . Implement best practices for data governance, security, and version control.

Analytics & Visualization

Collaborate with quantitative teams to translate financial models into production Python code. Create data visualizations and interactive dashboards with Power BI (or integrate BI outputs with Python services).

Collaboration & DevOps

Work with cross-functional teams (data scientists, portfolio managers, DevOps) in an agile SDLC environment. Use Git / GitHub, CI / CD, and containerization (Docker / Kubernetes) for deployment and version management.

Required Skills & Experience

• Strong proficiency in Python (Pandas, NumPy, FastAPI / Flask / Django).
• Experience with AWS S3 , Snowflake , and relational / columnar databases (SQL).
• Hands-on knowledge of data science workflows (data wrangling, statistical modeling, basic machine learning).
• Familiarity with Power BI or equivalent visualization tools.
• Understanding of financial analytics concepts such as performance attribution, portfolio risk, and alternative investment products (or willingness to learn quickly).

Nice to Have

Education

Bachelor s or Master s in Computer Science, Data Science, or related technical discipline.