Full Stack Data

Senior Full Stack Data Engineer – Enterprise Analytics Platform Location: Remote (Preference for India-based candidates) Compensation: Competitive salary + significant equity package ContexQ, a Singapore-based B2B SaaS AI startup, is dedicated to transforming financial crime, fraud, and risk management through a groundbreaking contextual decision intelligence platform. It processes billions of data points from various sources using Symbolic AI, Vector Search, Graph AI, and Agentic frameworks to deliver transparent, ethical, and actionable insights to clients. Our mission is to empower organizations with unparalleled intelligence while maintaining the highest standards of integrity and societal impact. This is an opportunity 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. By joining us, you will help build a NextGen Contextual Decision Intelligence Enterprise Analytics Platform that will set a new standard for explainable AI (XAI) in high-stakes industries. We’re seeking a passionate and sharp Full Stack Data Engineer to architect and build the front-end and back-end systems for the ContexQ’s 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. The role involves solving intricate technical challenges, from very large data processing to interactive graph visualizations. Frontend & Visualization (15%) Build responsive, scalable web applications using React and TypeScript for enterprise analytics and data visualization. Optimizing frontend performance for real-time exploration of large, multi-dimensional datasets Designing interfaces for explainable AI. Backend & API Development (35%) Develop and orchestrate micro-services using Node.js, Python or an equivalent language. Build and maintain data transformation and aggregation pipelines, optimizing for low latency and high throughput. Integrate with backend analytics powered by the Apache Spark eco-system. Use custom graph query language and SDKs to expose graph analytics capabilities. Cloud Infrastructure & Data Platform (50%) Deploy, scale, and monitor services on GCP using services such as Managed Airflow, Kubernetes with GKE, Cloud Run, etc. Implement cloud functions and serverless analytics workflows. Design and optimize large-scale data processing pipelines handling terabytes of data with Apache Spark. A Master's in Computer Science or a related field is preferred. Excellent communication skills for explaining complex technical ideas to non-technical audience Solid understanding of software engineering best practices and design patterns At least 4 to 6+ years of experience as a full-stack engineer in analytics, big data, or enterprise environments. Strong hands-on experience with Node.js, Java, Python or equivalent. Proficiency with AWS or GCP services such as EKS / GKE, Kinesis / Kafka / Pub/Sub, BigQuery / RedShift, and Lambda functions / Cloud Run. Proficiency in API design (GraphQL/REST/gRPC) with AI Gateways and containers based micro-services. Experience deploying and managing services on cloud platforms (AWS/Azure/GCP) using Terraform and containerised services with Docker and Kubernetes. Experience with major databases (SQL, NoSQL) and cloud based data warehouses (RedShift. BigQuery, Snowflake) Preferred Experience: Experience with distributed data processing and machine learning frameworks such as Apache Spark and Ray, and proficiency in Scala or PySpark. Hands-on work with enterprise analytics, operational intelligence, or business reporting platforms. Experience with graph-based data modelling, entity resolution, or custom database architectures would be a plus. Visual interactive exploration of enterprise networks with millions of entities Analytics Dashboards : Real-time operational, risk, and business metric monitoring processing TB of data Visualize supply chain, ESG, and other key KPIs with sub-second response Navigate and analyze hidden relationships in enterprise data using our proprietary graph engine This is an opportunity to solve intricate technical challenges and build a platform that fights financial crime. Innovation : The role offers the chance to work on proprietary graph technology, big data pipelines, and cutting-edge AI technologies. Growth : You'll also have the opportunity to influence core engineering and play a central role in building the early team. It offers continuous learning opportunities and mentorship from senior Data Analytics & AI practitioners. Flexibility & Equity : The company offers a competitive compensation, significant early-stage equity, learning resources, and a high-impact remote-first culture. Join us in building the next generation of enterprise analytics Includes full-stack, big data, and cloud architecture # Build a complex data visualization or analytics component #