Senior Full Stack Enterprise Analytics Engineer

Enterprise Analytics Engineer Opportunity

We are seeking a passionate and sharp Full Stack Developer to join our team in architecting and building the front-end and back-end systems for our platform. You'll work closely with our AI Engineers to create a scalable, intuitive platform that visualizes complex network relationships, delivers real-time risk scores, and integrates with advanced AI models.

This is a chance to solve intricate technical challenges, from real-time very large data processing to interactive graph visualizations, while contributing to a mission that fights financial crime, builds customer intelligence, and promotes ethical decision-making.

Role Overview

We are looking for an experienced Full Stack Engineer to drive the development of user-facing solutions built on our custom graph database and high-performance analytics engine. You will work with advanced backend technologies—Hadoop, Apache Spark, and Scala—to deliver high-impact data applications, real-time dashboards, and intuitive interfaces that make complex analytics accessible to business users.

This role requires building systems that handle visualization of graphs with millions of nodes, deliver sub-100ms API response times at scale, and process TB-scale datasets in real-time.

Key Responsibilities

• Frontend & Visualization (40%)
  • Build responsive, scalable web apps for advanced enterprise analytics and data visualization
  • Develop interactive graph/network visualizations capable of rendering millions of nodes and edges smoothly
  • Optimize frontend performance for real-time exploration of large, multi-dimensional datasets
  • Design interfaces for explainable AI and complex entity relationship analytics
  • Implement advanced rendering techniques (WebGL, canvas virtualization) for massive dataset visualization
• Backend & API Development (35%)
  • Architect and implement fast, scalable GraphQL/REST APIs with sub-sec response times for analytics, entity resolution, and graph queries
  • Develop and orchestrate microservices using Node.js, Python, Scala
  • Build and maintain data transformation and aggregation pipelines, optimizing for low-latency and high throughput
  • Integrate backend analytics powered by Apache Hadoop, Spark, and our proprietary graph database
  • Work with our custom graph query language and SDKs to expose graph analytics capabilities
• Cloud Infrastructure & Data Platform (25%)
  • Deploy, scale, and monitor services on GCP (Kubernetes, GKE, Cloud Run, Pub/Sub)
  • Implement cloud functions and serverless analytics workflows
  • Design and optimize large-scale data processing pipelines handling TB-scale data with Apache Hadoop and Spark
  • Collaborate with data engineers on ETL processes, data architecture, and real-time data integration strategies
  • Ensure platform reliability with 99.9% uptime SLAs

Requirements

Technical Skills

• At least 5–8+ years' experience as a full stack engineer in analytics, big data, or enterprise environments
• Strong hands-on experience with React, TypeScript, D3.js, WebGL, Node.js, Python, Scala
• Advanced expertise with Hadoop and Apache Spark for distributed data processing and analytics
• Experience building rich data visualizations and enterprise dashboards handling millions of data points
• Proficient in API design (GraphQL/REST), microservices, and optimizing for real-time and large-scale data flows
• Database exposure: PostgreSQL, Redis, Elasticsearch; experience designing or scaling custom graph engines a plus
• GCP experience with services like GKE, Pub/Sub, BigQuery, and Cloud Run

DevOps & Deployment

Enable Scalable Deployment: Deploy and manage services on cloud platforms using Docker and Kubernetes, optimizing for low-latency (