Lead Enterprise Data Architect

1 week ago

Belgaum, Karnataka, India beBeeDeveloper Full time ₹ 60,00,000 - ₹ 80,00,000

As a key member of our team, you will be responsible for designing and building the front-end and back-end systems for our platform.

About Us

We're redefining how organizations tackle financial crime, fraud, and risk management through a contextual decision intelligence platform.

We process trillions of data points from corporate registries, ESG, SDG, and supply chain data to deliver transparent, ethical, and actionable insights.

The Opportunity

This is an exciting opportunity to join our company and contribute to the development of 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.

Key Responsibilities
  • Frontend Development:
  • Build responsive, scalable web apps using React/TypeScript 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 Development:
  • 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.
  • Data Infrastructure:
  • 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.

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