Senior Business Analyst, Sales Compensation Analytics
At a glance
Senior Revenue & Sales Operations role at NetApp. Bangalore.
Pay not stated
growthroles summary, based on the employer's posting.
What you'll do
- Find repetitive work across business processes and automate tasks such as data checks, reporting, reconciliations and exception handling
- Build AI-assisted workflows and agents, then turn business needs into scalable designs, data models, tests and production solutions
- Create forecasts, scenario models and dashboards that help business and executive teams make decisions
- Work with IT and architecture teams on integrations, APIs, data movement and production scalability
- Set up audit and monitoring controls, investigate process or data problems, and train teams to use automation tools
What you bring
- At least eight years in business analysis, finance analytics, operations, data engineering or another listed function
- Hands-on automation experience using AI agents, generative AI and workflow tools
- Strong skills in analysis, modeling, visualization and troubleshooting across SQL, Excel, APIs and ETL
- Experience gathering requirements, mapping processes, designing solutions, testing and training teams on new tools
Who this fits
This senior role suits someone who can connect business analysis, financial or operational data, and automation delivery. The role is based in Bangalore, India.
From the employer
Job Summary
Partner with Finance, Operations, IT, business teams and leadership to identify automation opportunities, redesign processes and deploy solutions using the latest technology. The role will eliminate manual effort wherever practical, build reusable analytical tools, and train teams to confidently adopt and use new automation capabilities.
Job Requirements
· Identify, prioritize, and automate all types of repetitive or manual work across business processes, including data preparation, validations, reconciliations, reporting, documentation and exception management.
· Design and deploy AI agents, GenAI-enabled workflows and latest industry best solutions that improve accuracy, transparency, control and cycle time.
· Translate business requirements into scalable process designs, data models, workflow logic, user stories, test scenarios, and production-ready solutions.
· Build forecasting, scenario and what-if models; create dashboards and decision support for business and executive audiences.
· Partner with IT and enterprise architecture teams on APIs, ETL, middleware, system integrations, data lineage and production scalability.
· Establish monitoring, audit, acceptance and reconciliation controls; perform root-cause analysis and drive sustainable resolution of process and data issues.
· Develop practical playbooks and deliver hands-on training so teams can use Claude, Python and other approved automation tools safely and effectively.
· Document process flows, business rules, solution designs, test evidence, version history and production approvals.
Required Skills & Experience
Automation & AI: Demonstrated experience automating processes using the latest technologies, including AI agents, GenAI and workflow tools.
Data & Analytics: Strong data analysis, modeling, visualization, SQL/Excel, API, ETL and integration of troubleshooting skills.
Enablement: Experience training teams, creating user guidance and driving adoption of new tools and automated ways of working.
Tools: Hands-on experience with Claude, Python and industry-standard analytics, automation, integration and business intelligence tools.
Business Analysis: Strong requirements gathering, process mapping, solution design, testing, change management and stakeholder management.
Leadership Communication: Ability to explain technical and financial concepts clearly and provide concise, executive-ready recommendations.
Preferred Qualifications
Bachelor's degree in business, Finance, Data Science, Computer Science, Analytics, Information Systems or related fields. 8+ years of relevant experience in business analysis, finance analytics, operations, data engineering, process transformation, or enterprise automation. Exposure to machine learning, predictive analytics, enterprise AI governance and production-grade automation is preferred.
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