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 Requirements
- 5-8 years of professional fullstack/software engineering development experience with demonstrated ownership of endtoend systems.
- Proven experience designing, developing, and maintaining modern full-stack applications across both frontend and backend technologies.
- Strong frontend development expertise with React or Angular, TypeScript, JavaScript (ES6+), HTML5, and CSS3.
- Strong backend development experience using Python and modern frameworks such as FastAPI, Flask, or Django.
- Hands-on experience building and consuming REST APIs, developing microservices, and implementing event-driven architectures.
- Strong SQL skills with experience developing analytical queries against large-scale datasets.
- Experience with relational and NoSQL databases, including PostgreSQL, MySQL, MongoDB, or equivalent technologies.
- Exposure to deploying applications in Cloud using CI/CD methodologies including Git-based development workflows.
- Exposure building and deploying applications on Cloud platforms (Google Cloud Platform (GCP) preferred, including BigQuery, Composer (Airflow), Cloud Storage, Pub/Sub, Dataproc, Dataflow and GKE).
- 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.
Preferred Qualifications
- Experience working with Data Quality, Data Governance, Data Observability, or Data Management platforms.
- Experience with Terraform and Infrastructure-as-Code is highly preferred.
- Knowledge of Data Quality rules, metadata-driven systems, and monitoring frameworks.
- Experience developing dashboards using Power BI or modern visualization frameworks.
- Exposure to data engineering concepts and cloud-based data platforms.
- Familiarity with analytics and monitoring solutions for large-scale distributed systems.
- Experience supporting enterprise data products or data-driven platforms.
- Experience using AI-assisted engineering tools such as GitHub Copilot/Gemini/Claude/Cursor, or similar developer productivity platforms.