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Email [email protected] with resume to apply!

Location: Remote or Hybrid (Global)

Compensation: $210,000

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Role Overview:

We are seeking a talented and highly motivated Data Engineer to join our team. You will play a critical role in designing, building, and maintaining the robust data infrastructure required for developing, testing, and deploying quantitative investment algorithms. This role bridges the gap between raw financial data and advanced modeling, enabling our quants and data scientists to operate efficiently and effectively.

Key Responsibilities:

• Develop, maintain, and optimize data pipelines that ingest and process large volumes of structured and unstructured financial data from multiple sources (market data, alternative data, etc.).
• Design scalable ETL/ELT workflows to ensure high-quality, clean, and timely data availability for quantitative research and algorithm development.
• Collaborate closely with quantitative researchers, data scientists, and software engineers to understand data requirements and support model development and backtesting.
• Implement data validation and monitoring systems to ensure data accuracy and integrity.
• Build and maintain data storage solutions (data lakes, warehouses) optimized for analytical workloads.
• Automate repetitive data processing tasks to improve operational efficiency.
• Stay current with emerging data engineering technologies and best practices to enhance the fund’s data infrastructure.

Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Proven experience (3+ years) in data engineering, preferably in finance, fintech, or quantitative research environments.
• Strong programming skills in Python, SQL, and experience with data processing frameworks such as Apache Spark, Kafka, or similar.
• Experience with cloud platforms (AWS, GCP, Azure) and cloud-native data tools.
• Deep understanding of data modeling, database design, and performance tuning.
• Familiarity with financial market data, alternative data, and quantitative finance concepts is a plus.
• Ability to work independently in a fast-paced, collaborative startup environment.