Description

Responsibilities

• Design, build, and deploy high-performance full-stack applications and analytics tools to support quantitative research and fund management.
• Conduct proofs-of-concept (POCs) to validate architectural design patterns and deploy resilient, observable, and secure production systems on AWS.
• Work side-by-side with product owners, quantitative researchers, and cross-functional engineers to translate complex investment logic into scalable software.
• Ensure high standards across system resilience, observability (monitoring and logging), data security, and automated CI/CD pipelines.
• Facilitate and participate in departmental tech talks and knowledge-sharing initiatives to drive modern cloud adoption.

Qualifications

• Required
  • Strong expertise in Python software engineering and data libraries including NumPy, Pandas, Scikit-learn, and Dask.
  • Experience with Python frameworks and SDKs: Flask, Boto3, Dash.
  • Hands-on experience with relational and analytical databases: PostgreSQL and AWS Athena.
  • Proficiency with data pipelines and ingestion tools: AWS Glue ETL, S3, and data caching strategies.
  • Proven hands-on experience designing and operating cloud architecture using AWS services including EC2, ECS, AWS Lambda, Step Functions, SNS, and SQS.
  • Experience with AWS CloudWatch and SageMaker.
  • Strong grounding in microservices design, RESTful API Gateway implementation, and secure API integration.
  • Experience developing modern, responsive front-end interfaces using React and/or Dash.
  • Experience handling web application session states, Okta integrations, and secure authentication flows hosted on AWS.
  • Hands-on experience with continuous integration and delivery tools, including Bitbucket, Bamboo, Artifactory, and Ansible.
• Preferred
  • Prior experience or strong interest in financial services, asset management, capital markets, or equities trading

Key Skills

Education

Bachelor's degree