Senior Manager - Data Intelligence And Automation

JOB TITLE

Senior Manager - Data Intelligence & Automation | Holding | Strategy

Role Summary

The Senior manager of Data Intelligence & Automation is responsible for leading, defining and executing MAF unified BI and automation strategy that drives enterprise-wide data adoption, operational efficiency, and strategic insights. This role leads and oversees the development and governance of MAFHs Strategic Business Intelligence Platform, ensuring high data quality, platform scalability, and cross-functional alignment, while championing data literacy and self-service BI.

ROLE PROFILE

• Lead, define and execute a unified business intelligence strategy aligned with the organizations goals.
• Lead the development of MAF unified BI glossary, best practices and metadata repository to ensure clarity and consistency in reporting metrics and dimensions across MAF BUs
• Design, develop & maintain the platform for MAFH Strategic Business Intelligence Unit (SBIU).
• Manage CI/CD pipelines for seamless updates and enforce governance-compliant models’ structures (Row-Level Security).
• Drive, implement and advise on AI-Driven Solution and automation of business processes through to increase productivity and optimize costs.
• Identify areas for automation within reporting, data preparation, and business operations.
• Lead the advisory to provide best practices for cross-functional teams of BI leads, data scientists, and automation developers in delivering actionable insights and scalable solutions.
• Monitor BI adoption and continuously enhance user experience through training, support, and performance tuning.
  
  

• Education: Bachelor’s degree in data engineering, Computer Science, or MIS.
• Strong knowledge of data management, data architecture, processing, analytics, and IoT systems.
• Proficiency in Python (Pandas, APIs, ML with scikit-learn, TensorFlow).
• GenAI capabilities, including NLP, Retrieval-Augmented Generation (RAG), and LLM prompting.
• Implementation experience on AWS, Microsoft Cloud, Databricks, and Power BI.
• Integration experience with LLM APIs, vector databases, and retrieval pipelines