Job Title: Data Scientist Engineer

Location: New York, NY (Onsite – 5 Days per Week)

Company: High-Frequency Trading Firm

About the Role

We are seeking a Data Scientist Engineer to join our engineering and quantitative infrastructure team in New York City. This role sits at the intersection of data engineering, analytics, and quantitative research, supporting the development of high-performance data systems used for trading and market analysis. The ideal candidate has strong experience building scalable ETL pipelines, working with large financial datasets, and writing efficient Python and SQL in low-latency environments.

Responsibilities

Design, build, and maintain scalable ETL pipelines that process large volumes of financial market and trading data
Develop high-performance data infrastructure using Python and SQL to support quantitative research and trading systems
Ingest, clean, and transform structured and unstructured datasets including market data, order book data, and alternative data sources
Collaborate with quantitative researchers and trading teams to deliver reliable datasets and analytics tools for strategy development
Optimize data workflows and query performance across distributed data systems
Build automated data validation, monitoring, and alerting frameworks to ensure high data quality and reliability
Implement robust data models and storage solutions optimized for high-throughput financial data environments
Work closely with infrastructure and engineering teams to improve pipeline reliability and system scalability

Required Qualifications

3+ years of experience in data engineering, data science engineering, or similar roles
Strong programming skills in Python for data processing, automation, and analytics
Advanced SQL skills with experience working on large-scale datasets
Experience designing and maintaining ETL pipelines in production environments
Experience working with large datasets in distributed or cloud-based systems
Strong understanding of data modeling, data quality, and pipeline orchestration
Experience working in Linux-based environments

Preferred Qualifications

Experience working with financial data, trading systems, or market data feeds
Familiarity with high-frequency trading environments or quantitative finance
Experience with technologies such as Spark, Airflow, Kafka, or similar distributed data tools
Experience supporting quantitative research teams or data-driven trading strategies
Background in mathematics, statistics, computer science, or a related technical field

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