Full Stack Engineering

Fractal Analytics•New York, NY

1d•$110,000 - $130,000

About The Position

Fractal is a strategic AI partner to Fortune 500 companies with a vision to power every human decision in the enterprise. Fractal is building a world where individual choices, freedom, and diversity are the greatest assets; an ecosystem where human imagination is at the heart of every decision. Where no possibility is written off, only challenged to get better. We believe that a true Fractalite is the one who empowers imagination with intelligence. Fractal has been featured as a Great Place to Work by The Economic Times in partnership with the Great Place to Work® Institute and recognized as a ‘Cool Vendor’ and a ‘Vendor to Watch’ by Gartner. As a Fullstack Engineer, you will help build end‑to‑end Data‑to‑Decision systems, working closely with Data Scientists, Data Engineers, Product Owners, and UX specialists. You will design backend services, build intuitive UI experiences, and contribute to highly scalable, production-ready systems.

Requirements

3–6 years of hands‑on experience building and deploying fullstack applications at enterprise scale.
Expert-level proficiency in Python (3.4+)
Strong experience with at least one backend stack: Python / Node.js / Java / Ruby / PHP / .NET
Designing, building, and consuming REST APIs.
Experience with PySpark for: Distributed data processing, Transformations and ETL workflows, Integration with analytics pipelines, Optimizing Spark jobs and performance tuning
Familiarity with CI/CD pipelines, particularly in Azure Cloud environments.
Python and/or Java application development
API development (REST, HTTP, JSON, authentication patterns)
Advanced SQL (complex queries, DDL, data modeling, performance tuning)
Microsoft Azure: Functions, Synapse, Data Factory, Azure DevOps, CI/CD and Git

Nice To Haves

Snowflake or Databricks
Data quality and validation frameworks
.NET experience
PySpark and distributed data processing

Responsibilities

Design, develop, and maintain frontend and backend components across multiple enterprise-grade platforms.
Integrate machine learning and analytics outputs from backend REST APIs into responsive UI workflows.
Build dynamic dashboards, data visualizations, and interactive UI components for business stakeholders.
Participate in UAT, debug cross-system issues, and resolve performance bottlenecks.
Diagnose and troubleshoot bugs, API failures, and application integration issues.
Develop documentation for APIs, application workflows, and system integrations.
Collaborate with DS/DE teams on data pipelines where needed, especially involving PySpark data processing.