Java Fullstack Engineer with AI

URGENT REQUIREMENT Python Full-Stack Engineer Location : NYC, NY Duration : 6 +months Onsite position We are seeking a motivated engineer with strong full-stack data engineering skills to join our innovative, dynamic team. This role focuses on building reliable, scalable data products and user experiences that power AI / ML modelling, agentic workflows, and reporting. You will work end-to-end - from data ingestion and transformation through to UI - to deliver production-grade solutions in a collaborative, fast-paced environment. Our application stack runs entirely on AWS and includes Angular for the frontend; Python / Django with AWSmanaged PostgreSQL (RDS / Aurora) for the API layer; Elasticsearch for search; SageMaker for machine learning; and Python / Celery for background processing. We also leverage Terraform for infrastructure as code, GitHub Actions for CI / CD, and Kubernetes (EKS) for container orchestration. We are investing heavily in our data architecture, leveraging Snowflake, data transformation tooling (e.g. dbt), and modern data ingestion frameworks.

Key Responsibilities :

• Collaborative development : - partner with business stakeholders, data scientists, and engineering teammates to define and adopt modern data engineering practices.
• Full-stack data engineering : - build across the entire stack, including data ingestion / acquisition and transformation, APIs, front-end components, and automated test suites.
• Specification and design : - translate short- and long-term business requirements, architectural considerations, and competing timelines into clear, actionable specifications.
• Code quality : - write clean, maintainable, efficient code that adheres to evolving standards and quality processes, including unit tests and isolated integration tests in containerized environments.
• Continuous improvement : - contribute to agile practices and provide input on technical strategy, architectural decisions, and process improvements.

Required Skills & Experience :

Education :

Bachelor s or Master s degree in Computer Science, Statistics, Informatics, Information Systems, or a related quantitative field.

Preferred Skills & Experience :