About the role
The Role:
We are seeking a highly motivated Senior Technical Business Analyst with a strong understanding of modern data platforms, cloud-native architecture, DevOps practices, and Data Engineering principles. The ideal candidate will serve as a bridge between business stakeholders, product teams, and engineering organizations to deliver scalable, data-driven solutions. This role will partner with Data Quality, Data Engineering, Product, Operations, and Business stakeholders to define, measure, monitor, and improve the quality of critical business data assets across the enterprise.
The successful candidate will play a key role in translating business objectives into actionable requirements, supporting data quality standards definitions and rules, supporting analytics and reporting, and helping drive continuous improvement initiatives across D&B's data ecosystem while identifying opportunities to leverage Agentic AI and intelligent automation to improve operational efficiency and business outcomes.
Key Responsibilities:
- Partner with business stakeholders, product owners, and engineering teams to gather, analyze, and document business, data, and technical requirements.
- Translate requirements into user stories, acceptance criteria, process flows, data mappings, and functional specifications for Data Engineering and Data Quality solutions.
- Collaborate with Data Engineering teams to define data quality rules, data models, pipeline requirements, governance standards, and observability metrics.
- Work closely with DevOps and platform teams to support CI/CD, monitoring, operational excellence, and platform reliability practices.
- Analyze data quality, operational, and business metrics, perform root-cause analysis, and drive continuous improvement initiatives.
- Identify opportunities to leverage Agentic AI, automation, and AI-assisted workflows to improve data quality, operational efficiency, and decision-making processes.
- Mentor and provide guidance to less experienced team members.
Key Requirements:
- 9+ years of experience as a Business Analyst, Technical Business Analyst, Data Analyst, or similar role in Data Engineering, Analytics, or Data Platform environments.
- Strong SQL skills with the ability to analyze large datasets, validate data quality rules, and perform root-cause investigations.
- Experience working in Agile/Scrum environments, including backlog management, story refinement, sprint planning, co-ordination with PM and acceptance criteria.
- Experience working with Data Engineers, Solution Architects, Product Owners, and Platform Engineering teams in large-scale cloud data environments.
- Working knowledge of Power BI, including designing, developing, and administering dashboards that provide insights from data quality monitoring and operational metrics.
- Experience with cloud-native data platforms, preferably GCP, including BigQuery, Dataflow, Dataproc, Composer/Airflow, Cloud Storage, and Pub/Sub.
- Strong understanding of modern Data Engineering architectures, data pipelines, observability, and DevOps best practices.
- Familiarity with Data Quality, Data Governance, Metadata Management, Data Observability, Data Lineage, and Data Cataloguing frameworks.
- Experience leveraging Generative AI, AI copilots, or Agentic AI solutions to automate business processes, data analysis, documentation, monitoring, or operational workflows.
- Understanding of AI/LLM concepts, prompt engineering, retrieval-augmented systems, MCP/A2A protocols, or agent-based orchestration frameworks is highly desirable.
- Strong verbal and written communication skills, with the ability to articulate complex data issues and solution recommendations to both technical and business audiences.
- Experience collaborating across time zones as part of a global team.
