Join a full-stack engineering team supporting the Quantitative Equity Group’s (QEG) cloud-native signal generation, backtesting, data, and analytics platforms. These critical systems drive active, factor, and alternate strategy fund operations across front-, middle-, and back-office environments.
In this role, you will build next-generation quantitative research platforms on AWS, collaborate closely with investment business partners and product owners in an Agile setting, and gain direct exposure to global investment trading operations.
Qualifications & Technical Requirements
Core Backend & Data Stack
Python Development: Strong expertise in Python software engineering and analytics/data libraries:
Data processing & analytics: NumPy, Pandas, Scikit-learn, Dask
Frameworks & SDKs: Flask, Boto3, Dash
Data Architecture & Storage:
Relational & Analytical Databases: PostgreSQL, AWS Athena (plus)
Data Pipelines & Ingestion: AWS Glue ETL, S3, data caching strategies
AWS Cloud & Serverless Infrastructure
AWS Services: Proven hands-on experience designing and operating cloud architecture using:
Compute & Containers: EC2, ECS
Serverless & Orchestration: AWS Lambda, Step Functions, SNS, SQS
Machine Learning & Observability: SageMaker, CloudWatch
API & Microservices Architecture: Strong grounding in microservices design, RESTful API Gateway implementation, and secure API integration.
Front-End & Authentication
Web Development: Experience developing modern, responsive front-end interfaces using React and/or Dash.
Identity & Session Management: Experience handling web app session states, Okta integrations, and secure authentication flows hosted on AWS.
DevOps & CI/CD
Hands-on experience with continuous integration and delivery tools, including Bitbucket, Bamboo, Artifactory, and Ansible.
