Senior Data Engineer

The Hagen Ricci Group; New York (NY); Hybrid; USD 90,000 - 150,000; Full time

Job summary

An established industry player seeks a Senior Data Engineer to join their innovative team. In this pivotal role, you will develop and maintain scalable Python-based ETL pipelines, design high-performance database schemas, and build cloud data lake solutions using AWS and Databricks. Collaborating closely with portfolio managers and quantitative researchers, you'll tailor data solutions that drive trading insights and risk management. This position offers the opportunity to work in a dynamic environment where your contributions will significantly impact the firm's data infrastructure and analytics capabilities.

Qualifications

• Experience with Python and ETL processes for market data.
• Knowledge of AWS and Databricks for cloud data solutions.

Responsibilities

• Develop scalable Python-based ETL pipelines for market data.
• Design relational and NoSQL database schemas for analytics.
• Build cloud data lake solutions for structured and unstructured data.

Skills

Python

ETL Pipelines

AWS

Databricks

Data Quality

Data Analysis

Tools

NoSQL Databases

Relational Databases

Job description

Global multi-strat hedge fund is looking for a senior data engineer to work with Systematic portfolio managers. Experience working with Security Master is preferred but not required.

Responsibilities

1. Develop and maintain scalable Python-based ETL pipelines for ingesting and transforming market data from multiple sources.
2. Design and optimize relational and NoSQL database schemas to support high-performance analytics and improve overall data platform infrastructure.
3. Build and manage cloud data lake solutions (AWS/Databricks) for storing and retrieving large volumes of structured and unstructured data.
4. Implement rigorous data quality, validation, and cleansing routines to ensure the accuracy of financial time-series data.
5. Optimize data workflows for low latency and high throughput, critical for quantitative research, trading strategies, and risk management.
6. Collaborate with portfolio managers, quantitative researchers, and traders to tailor data solutions that support modeling, strategy development, and trading insights.
7. Develop data mapping and normalization solutions to incorporate data into the firm’s centralized security master.
8. Analyze and extract insights from datasets to inform trading and risk management decisions.
9. Document system architecture, data flow processes, and technical solutions to ensure transparency and reproducibility.

Interested candidates can contact us at: [e-mail]

Reference: DF609

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