Data Scientist (R-19247)
Eyeota
Data Science
Hyderabad, Telangana, India
Posted on May 14, 2026
Shape the Future with Dun & Bradstreet
At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. For over 180 years, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers.
The Role:
Data Quality Agentic Systems Engineer is responsible for designing and building intelligent, agent-based systems that transform how data quality is measured, monitored, and acted upon across D&B’s global platforms and products.
This role goes beyond traditional automation to create adaptive, decision-capable systems that can reason over data quality signals, orchestrate actions, and support proactive data quality management at scale.
Key Responsibilities:
- Design and build agentic and AI-enabled systems to support data quality measurement, monitoring, and remediation.
- Develop intelligent agents capable of:
- Interpreting data quality signals and metrics
- Coordinating workflows across systems
- Supporting root cause analysis and decision-making
- Partner with Data Quality Insights leadership to translate strategic measurement goals into agent-based solutions.
- Integrate large language models (LLMs) and AI services responsibly into data quality workflows.
- Build frameworks that allow agents to interact with:
- Data quality rules and metrics
- Metadata, lineage, and monitoring systems
- Human-in-the-loop review and governance processes
- Apply data observability and anomaly detection concepts to improve detection, prioritization, and root‑cause analysis.
- Ensure agentic systems are observable, auditable, and aligned with enterprise risk and compliance expectations.
- Collaborate with business and technical stakeholders to ensure data quality intent and requirements are accurately represented in agent logic.
- Utilize PowerBI and/or Looker dashboards and reporting outputs as inputs and feedback mechanisms for agent behavior.
- Communicate with globally distributed stakeholders using JIRA and Confluence.
- Develop comprehensive documentation of agent architectures, behaviors, and data quality outcomes.
- Generate insights and recommendations based on data quality signals and agent outputs.
- Establish best practices for agent design, evaluation, and lifecycle management within Data Quality Insights.
- Provide technical guidance and mentorship to other engineers within the Data Quality Insights organization.
- Remain current with industry best practices and emerging technologies related to data quality and intelligent systems.
Key Requirements:
- Bachelor’s degree in computer science, engineering, or equivalent experience.
- Advanced experience in software engineering, data engineering, or applied AI systems.
- Strong proficiency in SQL and Python within complex data environments.
- Experience designing complex, distributed, or intelligent systems.
- Solid understanding of data quality concepts and enterprise data ecosystems.
- Experience with cloud computing technologies (preferably GCP).
- Strong analytical, problem‑solving, and communication skills.
- Ability to work independently and collaborate effectively across globally distributed teams.
All Dun & Bradstreet job postings can be found at https://jobs.lever.co/dnb. Official communication from Dun & Bradstreet will come from an email address ending in @dnb.com.
Notice to Applicants: Please be advised that this job posting page is hosted and powered by Lever, a subsidiary of Employ Inc. Your use of this page is subject to Employ's Privacy Notice and Cookie Policy, which governs the processing of visitor data on this platform.
