About the Project
The project builds reusable platform capabilities and data products that help quantitative researchers discover, access, and consume data across a complex, disparate landscape, and accelerate successful prototypes into production.
Responsibilities
•Design, build, and enhance data pipelines and integration frameworks for AI, analytics, and business applications
•Improve data quality, reliability, lineage, and monitoring
•Use AI agents as a primary tool to design, build, test, and support solutions
•Collaborate with business stakeholders, product managers, and engineering teams to translate business objectives into technical solutions
Requirements
•10+ years of professional software development experience, including 5+ years in data engineering
•Advanced proficiency in Python, including building scalable backend services and data processing solutions
•Hands-on experience designing and implementing data pipelines, data integration solutions, and large-scale data processing architectures
•Experience with relational databases and modern data storage technologies, including graph, vector, or analytical data platforms
•Practical experience building and deploying AI/LLM-enabled applications in production
•Experience with LangGraph, LangChain, agentic workflows, or AI application orchestration frameworks and evaluations
•Familiarity with modern AI tooling, workflows, and AI-assisted software engineering practices
•Experience in agile delivery environments
•Strong communication skills and ability to interact effectively with stakeholder groups, including business users
Nice to Have
•Experience with Databricks, Spark, Delta Lake, or similar data engineering platforms
•Experience with enterprise data lakes, lakehouses, or large-scale analytical platforms
•Experience in Investment Management, Asset Management, Capital Markets, or Financial Services
•Strong understanding of Fixed Income products and related investment workflows
•Experience with Aurora, Neptune, and other AWS data services
•Experience architecting, provisioning, and managing production infrastructure on AWS, including ECS Fargate, Lambda, SQS, and related cloud-native technologies
•Experience defining cloud architecture programmatically using IaC tools such as AWS CDK or Terraform
Conditions
Not specified in the posting.
