Fullstack Engineer

Dun & Bradstreet; Hyderabad; Hybrid; INR 3,000,000 - 5,400,000; Full time

Job summary

Dun & Bradstreet is seeking a high-caliber Full Stack Engineer to design, develop, and scale Data Quality and AI-enabled platforms. You will work across the stack from UI to data processing pipelines, partnering with Data Quality SMEs, Data Engineers, Product Managers, and Platform Teams to deliver observability, analytics, governance, and AI-driven insights.

Responsibilities include building modern web apps with React/TypeScript and Python (FastAPI), deploying cloud-native services on GCP, and

Qualifications

• 5-8 years of professional fullstack/software engineering development experience with end-to-end ownership.
• Strong frontend experience with React/Angular, TypeScript, JavaScript (ES6+), HTML5/CSS3.
• Strong backend experience using Python, FastAPI or Flask.
• Strong SQL skills and ability to write analytical queries on large datasets.
• Experience designing REST APIs and microservices architectures.
• Experience with Docker, CI/CD pipelines, Terraform, and Git workflows.
• Experience deploying on Google Cloud Platform (GCP) with BigQuery, Airflow (Composer), Cloud Storage, Pub/Sub, Dataproc, Dataflow and GKE.

Responsibilities

• Design and develop modern, responsive web apps and scalable full‑stack solutions.
• Build Data Quality and Analytics features including observability and governance workflows.
• Implement cloud-native solutions on GCP and containerize with Docker/Kubernetes.
• Integrate AI-powered capabilities and LLM-enabled services where applicable.
• Ensure code quality through automated tests and engineering best practices.
• Collaborate with cross-functional teams to deliver enterprise-grade solutions.

Skills

React/Angular

TypeScript

JavaScript (ES6+)

HTML5/CSS3

Python

FastAPI/Flask

SQL

REST APIs

Microservices

Docker

CI/CD

Terraform

Tools

Git

Kubernetes

GKE

BigQuery

Airflow

Terraform (IaC)

Job description

The Role:

We are seeking a highly skilled Full Stack Engineer to design, develop, and scale next-generation Data Quality and AI-enabled platforms. In this role, you will work across the entire technology stackfrom intuitive user experiences and data visualizations to cloud-native backend services and data processing pipelines. You will partner closely with Data Quality SMEs, Data Engineers, Product Managers, Data Scientists, and Platform Teams to build solutions that support data observability, analytics, data governance, and AI-driven insights.You will help build the next generation of D&B's Data Quality Insights platform, enabling data governance, observability, analytics, and AI-powered decision support for enterprise data products.

Key Responsibilities:

Full stack Application Development:

Design and develop modern, responsive web applications and drive the end-to-end development of scalable full-stack solutions using React, TypeScript, and Python(FastAPI), delivering high-performance web applications, APIs, microservices, analytics dashboards, data platform integrations, and AI-powered capabilities in partnership with Product, Data Engineering, Architecture, and Platform teams.

Data Quality & Analytics:

Build and enhance next-generation Data Quality and Governance platform that enables rule management, observability, metadata-driven monitoring, policy enforcement, and AI-powered insights. Develop scalable capabilities (front-end and back-end) for data quality assessment, anomaly detection, lineage, governance workflows, and self-service analytics, transforming business requirements into extensible enterprise-grade solutions.

Cloud Engineering & DevOps:

Build cloud-native applications using GCP. Containerize applications using GKE and orchestrate deployments through CI/CD pipelines, preferably Terraform. Implement Infrastructure-as-Code and engineering best practices. Participate in operational excellence activities, monitoring, reliability, and platform optimization.

AI & automation:

Integrate Generative AI and Agentic AI capabilities into engineering solutions. Collaborate with Data Scientists and AI teams to operationalize AI/ML models. Develop AI-powered workflows, anomaly detection solutions, and intelligent user experiences. Build and integrate LLM-enabled services, copilots, and automation capabilities where appropriate.

Engineering Governance:

Write clean, maintainable, and testable code. Develop automated unit, integration, and end-to-end tests. Perform code reviews, technical documentation and contribute to engineering standards and best practices. Champion security, scalability, performance, and accessibility standards. Participate in architectural discussions and comply to Agile/Scrum practices.

Key Requirements:

• 5-8 years of professional fullstack/software engineering development experience with demonstrated ownership of endtoend systems.


• Strong experience in modern frontend development using React/Angular, TypeScript, JavaScript (ES6+), HTML5/CSS3


• Strong backend development experience using Python, FastAPI or Flask


• Strong SQL skills with experience developing analytical queries against large-scale datasets.


• Experience designing and developing REST APIs, Microservices architectures, Event-driven systems


• Experience with databases PostgreSQL, MySQL, MongoDB or equivalent NoSQL technologies


• Experience with Docker, CI/CD pipelines, Terraform, Git-based development workflows


• Experience building and deploying applications on Google Cloud Platform (GCP) including BigQuery, Composer (Airflow), Cloud Storage, Pub/Sub, Dataproc, Dataflow and GKE. Experience with Terraform and Infrastructure-as-Code is highly preferred.


• Strong testing fundamentals across the stack (unit, integration, E2E).


• Solid understanding of Git workflows and development tooling (npm/yarn etc).


• Familiarity with data pipelines, ETL/ELT processing, metadata-driven architectures, observability frameworks, and large-scale analytical platforms.


• Strong grounding in web security, including authentication, authorization, and secure API communication.


• Strong problem-solving, communication, and collaboration skills.


• Ability to work independently and in cross-functional teams.


• Focus on quality, performance, and maintainability.