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Salary
≈ $13k – $29k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp

First seen by Alion on Aug 26, 2026.

Overview
Company
Impact
Profile match
Nineleaps are enablers of Digital Transformation across industries, helping partner companies become future ready.

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Responsibilities:

  • Analyze historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
  • Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
  • Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
  • Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
  • Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
  • Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

  • 3-6 years of experience in data analytics, business intelligence, data engineering, or a similar analytical role.
  • Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyze large datasets.
  • Experience working with Google Sheets and implementing automation through data pipelines or workflows.
  • Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
  • Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
  • Ability to collaborate effectively with remote and geographically distributed teams across different time zones.
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