Senior Business Analyst

Key Responsibilities

• Work 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.
• 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

• 7+ years of experience as a Business Analyst, Technical Business Analyst, or similar role in Data Engineering, Analytics.
• 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, coordination 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.
• 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.