Quant Finance Data Engineer: Scalable Pipelines & ML-Ready

Wenna Holdings Inc.; Minnesota; On-site; USD 110,000 - 150,000; Full time

Job summary

Wenna Holdings Inc. is seeking a Financial Data Engineer to build and maintain scalable data pipelines for market and alternative data, ensuring our datasets are accurate, accessible, and actionable for investment decisions.

You will develop APIs and microservices to feed quantitative models and trading systems, optimize database performance, and collaborate with analysts to structure data for advanced analytics and machine learning, with rigorous data quality checks.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• 3+ years of experience in data engineering, preferably within the financial services industry.
• Expert proficiency in Python, SQL, and cloud platforms (AWS/GCP).
• Experience with time-series databases and large-scale data processing.
• Strong understanding of software engineering best practices.

Responsibilities

• Design, build, and maintain scalable data pipelines for market and alternative data.
• Develop APIs and microservices to deliver data to quantitative models and trading systems.
• Optimize database performance and ensure high availability of critical financial datasets.
• Collaborate with analysts to structure data for advanced analytics and ML.
• Implement rigorous data quality checks and validation protocols.

Skills

Python

SQL

Cloud AWS/GCP

Time-series databases

Large-scale data processing

Software engineering best practices

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, or related field

Tools

Spark

Hadoop

CI/CD pipelines

Infrastructure as Code

Job description

Wenna Holdings Inc. is seeking a Financial Data Engineer to build and maintain scalable data pipelines for market and alternative data, ensuring our datasets are accurate, accessible, and actionable for investment decisions.

You will develop APIs and microservices to feed quantitative models and trading systems, optimize database performance, and collaborate with analysts to structure data for advanced analytics and machine learning, with rigorous data quality checks.