Nineleaps is a boutique technology-consulting firm, that helps funded ventures and enterprises accelerate their product development and data efforts. We are 500+ people strong and based out of Bangalore, India. Over the past 10 years, our community of engineers has delivered over 200 intuitive and pragmatic solutions to our clients’ more complex challenges. We have gained multiple levels of expertise by working with market leaders, technology giants, and the latest disruptors of many industries such as Retail, e-Business, Advertising, Finance, Transportation, Healthcare, and Education.
We are looking for a Senior Data Analyst to join our team.
Primary Responsibilities:
Build and maintain dashboards, reports, and models to track sales metrics, trends, and performance across segments.
Analyze sales data and workflows to identify opportunities for improvement and recommend actionable strategies for growth.
Support sales forecasting, capacity planning, and target setting through data-driven projections and market insights.
Collaborate with BI and data teams to ensure data accuracy and develop scalable solutions using SQL, Python, and visualization tools (Tableau, Power BI).
Assess funnel performance and conversion efficiency to identify bottlenecks and suggest process improvements.
Conduct deep-dive analyses to address critical business questions and support strategic decision-making.
Desired Skills:
5+ years of experience in Sales Operations, BI, or Data Analytics, preferably in Grocery, Retail, E-commerce, or Q-commerce.
Strong ability to translate complex data into actionable insights and present to senior leadership.
Proficiency in SQL, data visualization tools (Tableau, Power BI, Looker), and analytical programming (Python/R).
Experience with CRM systems like Salesforce and understanding of sales data structures.
Excellent analytical, problem-solving, and quantitative skills with high attention to detail.
Strong communication and interpersonal skills to engage and influence cross-functional teams.
Bachelor’s degree in Business, Economics, Finance, Statistics, Computer Science, or related field; Master’s/MBA preferred.
Data Engineering
