MIS AUTOMATION

Key Responsibilities:

1. Report Automation:

   • Design, develop, and maintain automated reporting systems to streamline report generation and distribution processes.
   • Utilize scripting languages (e.g., Python, R) and tools (e.g., SQL, ETL tools) to automate data extraction, transformation, and loading (ETL) processes.

   • Data Management:

   • Ensure the integrity, accuracy, and timeliness of data used in reports.
   • Develop and manage data pipelines and workflows to support automated reporting.

2. Report Design and Development:

   • Create and customize reports and dashboards to meet business requirements using tools like Tableau, Power BI, Excel, or similar.
   • Ensure that reports are user-friendly and effectively communicate key insights to stakeholders.

3. Process Improvement:

   • Identify opportunities for process improvements and automation within reporting workflows.
   • Implement best practices for report automation and data handling to enhance efficiency.

4. Collaboration and Support:

   • Work closely with business analysts, data engineers, and other stakeholders to gather requirements and ensure alignment with business objectives.
   • Provide support and training to end-users on automated reporting tools and processes.

5. Quality Assurance:

   • Conduct thorough testing of automated reports and data pipelines to ensure accuracy and reliability.
   • Troubleshoot and resolve issues related to report generation and data automation.

Required Skills and Qualifications:

• Education:

  Bachelor s degree in Computer Science, Data Science, Mathematics, Statistics, Business Analytics, or a related field. Advanced degrees or certifications are a plus.

• Experience:

  • Proven experience in report automation and data analysis.
  • Proficiency in programming languages such as Python or R for automation tasks.
  • Experience with SQL for data extraction and manipulation.
  • Hands-on experience with reporting and visualization tools such as Tableau, Power BI, or Excel.

• Technical Skills:

  • Strong understanding of data management, ETL processes, and database systems.
  • Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) is an advantage.
  • Knowledge of scripting and automation tools (e.g., Bash, PowerShell) is beneficial.

• Soft Skills:

  • Excellent analytical and problem-solving skills.
  • Strong attention to detail and ability to work with complex datasets.
  • Effective communication skills, both written and verbal.
  • Ability to work independently as well as part of a team.

Preferred Skills and Qualifications:

• Experience with advanced analytics or machine learning techniques.
• Familiarity with Agile or other project management methodologies.
• Experience in a similar industry or domain.