Data Engineer - Python

About the Role :

We are seeking a proactive and detail-oriented Data Engineer to build and maintain robust data processes for our financial datasets. You will play a pivotal role in designing data ingestion pipelines, ensuring data quality, and enabling seamless access for our quantitative research and trading teams.

Key Responsibilities :

Python Driven Data Pipelines :

- Develop, maintain, and optimize Python scripts and libraries for automated data ingestion from market data providers and internal sources.

- Develop and maintain a unified RPC-based data access library in Python, compatible with all key systems.

- Take complete ownership of identifying, auditing, and managing all existing and new data sources.

Data Quality & Monitoring :

- Design and deploy automated validation checks to detect anomalies, gaps, and inconsistencies in incoming data feeds.

- Collaborate with quants to establish data accuracy benchmarks and troubleshoot data discrepancies.

- Data Vendor Management & Pipeline Expansion

- Proactively source and evaluate new external data vendors and offerings (e.g., factor models, fundamental and sentiment data).

- Build and maintain a pipeline of potential and exploratory data sources.

- Monitor and ensure timely ingestion of data from all subscribed providers.

- Evaluate subscription utility to optimize costs (e.g., Refinitiv, eSignal, KRX). Conduct regular audits to reduce spend on underutilized or obsolete sources.

Collaboration & Documentation :

- Partner closely with quantitative researchers and software engineers to integrate new datasets and evolving requirements.

- Write clear documentation and maintain code repositories to support team onboarding and knowledge sharing.

Long-Term Data Strategy :

- Stay updated on industry trends in financial data and Python tooling to drive continuous enhancement of our data stack.

- Collaborate with research and engineering teams to define and compute proprietary indicators (e.g., custom sentiment scores).

Required Experience & Skills :

- 12 years of professional experience in data engineering, data analyst, software development or a Python focused role.

- Strong proficiency in Python scripting, including building functions, modules, and lightweight APIs.

- Experience with numpy and pandas packages.

- Familiarity with version control (Git) and collaborative development workflows.

- Basic understanding of financial market data (e.g., equities, derivatives) and the challenges of time series data.