Data/AI Engineer for quantitative research

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.

• 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

• 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
• Будет плюсом: Experience with Databricks, Spark, Delta Lake, or similar data engineering platforms; 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

• Условий в вакансии нет