Role Overview

As Lead Business Data Analyst, you will drive data analysis, engineering, and advanced analytics initiatives. You will collaborate with Data Product Managers, Data Owners, and global cross-functional teams to deliver impactful business outcomes. This role balances hands-on analytics, AI innovation, stakeholder engagement, and continuous process improvement.

Key Responsibilities

- Lead complex data analysis, modeling, and visualization activities to extract actionable insights and support strategic decision-making.
- Collaborate with Data Product Managers and business stakeholders to gather requirements, define analytics and AI-powered solutions, and ensure alignment with product and project goals.
- Identify opportunities where AI-powered solutions can enhance data insights, automation, and optimize business processes.
- Translate business requirements into technical features, epics, and user stories for Agile delivery, supporting delivery team as Scrum Master where required.
- Work closely with engineering teams to operationalize automated data pipelines and data science models while balancing technical dependencies and timely delivery.
- Document and improve data pipelines, processes, and data flows, ensuring quality, scalability, and security.
- Develop reports and self-service dashboards—clearly communicate complex findings, including AI-generated insights, to technical and non-technical audiences.




- Champion data governance, privacy, and responsible AI usage across analytics initiatives.
- Identify opportunities for simplification, optimization, and automation within data and AI workflows.
- Promote knowledge sharing by disseminating best practices, tools, and technical expertise across teams.
- Stay ahead of data and AI trends; promote the use of data analytics, generative AI and machine learning where appropriate.

Competencies

- Proficient with Agile methodologies and tools (eg. Jira, Confluence) for effective delivery.
- Ability to write detailed product requirements, user stories, and acceptance criteria for analytics and AI features.
- Experienced in managing backlogs based on business value, technical dependencies, and the potential impact of AI-driven features.
- Hands-on expertise in data analysis, modelling and visualization tools (eg. SQL, Python, PowerBI, Tableau).
- Proactive problem-solving, critical-thinking, and process improvement skills rooted in engineering mindset.
- Effective communicator: skilled at translating complex technical and AI concepts for diverse stakeholders, verbally and in writing.
- Ownership mindset: demonstrate accountability and commitment to delivering outcomes.
- Continuous learner: adapt to recent technologies and thrive in dynamic, fast-paced environments.

📌 Lead Data Analyst (Bengaluru)
🏢 Dyson
📍 Bengaluru