Operations MIS Data Analyst

About the role

The Operations MIS - Data Analyst is responsible for managing, analyzing, and reporting operational data to support decision‑making and enhance operational efficiency. The role involves extracting and transforming data, creating dashboards, tracking performance metrics, and automating reporting workflows.

Key responsibilities

• Design, develop, and maintain daily, weekly, and monthly MIS reports and operational dashboards.
• Extract, transform, and analyze operational data from various systems and databases.
• Track and analyze key operational metrics to identify trends, anomalies, and opportunities for process optimization.
• Ensure data accuracy, consistency, and integrity across all reports and reporting platforms.
• Automate recurring reporting processes using advanced Excel functions, VBA/Macros, or basic scripting to maximize efficiency.
• Collaborate cross‑functionally with Operations, IT, and Finance teams to satisfy data needs and resolve data issues.
• Prepare clear business presentations and executive summaries highlighting operational performance.
• Assist in the implementation and testing of new operational software or database upgrades.

Required profile

• Bachelor’s degree in Information Technology, Business Administration, Statistics, Computer Science, or a related field.
• 3‑4 years of proven experience in an MIS, Data Analyst, or Operations Reporting role.
• Advanced proficiency in Microsoft Excel (Pivot Tables, VLOOKUP/XLOOKUP, INDEX/MATCH, Power Query, and Macros/VBA).
• Hands‑on experience with data visualization tools such as Power BI or Tableau.
• Familiarity with SQL for database querying and data extraction (highly preferred).
• Strong analytical and problem‑solving skills with a keen eye for detail.
• Ability to translate complex data into clear, actionable business insights.
• Excellent communication and presentation skills.

Required skills

• Microsoft Excel (advanced, including Pivot Tables, Power Query, VBA/Macros).
• Power BI or Tableau for data visualization.
• SQL for database querying.