Database Administrator

We are seeking a Data Analyst with 3-4 years of hands-on industry experience in Power BI analytics, data modeling, and business insight delivery, supported by strong Python capability for data preparation, analysis, and automation.

This role is primarily focused on building and owning enterprise-grade Power BI dashboards used by stakeholders. The candidate must have delivered real production analytics solutions.

Power BI Development & Analytics

• Design, develop, and maintain Power BI dashboards and reports for KPIs and operational insights.
• Build robust data models (star schema, relationships, calculated tables).
• Develop advanced DAX measures and optimize for performance and usability.
• Implement Row-Level Security (RLS), refresh schedules, and governance best practices.
• Troubleshoot data quality issues, refresh failures, and performance bottlenecks.
• Own dashboard lifecycle: requirements → build → UAT support → deployment → enhancements.

Data Analysis, Automation & Preparation (Python + SQL)

• Use Python to clean, transform, and analyse datasets (e.g., pandas, numpy) and to automate recurring analysis/reporting tasks.
• Use SQL to extract, validate, and reconcile data across systems.
• Create reusable data preparation scripts and support dataset readiness for reporting.
• Perform root-cause analysis and explain “why” behind trends, not just “what”.

Data Storytelling & Executive Reporting

• Translate analysis into clear, actionable business insights.
• Produce professional PowerPoint decks that communicate trends, risks, and recommendations.
• Present insights to both technical and non-technical stakeholders with clarity.

Backend & Integration Support

• Support integration work using Node.js (e.g., REST APIs, data services, connecting to internal systems).
• Build or maintain simple services/scripts to enable data movement or analytics integration.
• Must be based on real implementation experience (not academic-only).

AI/ML Exposure

• Experience with machine learning algorithms and tools (e.g Pytorch, R, scikit-learn, TensorFlow, Python).
• Apply basic models where useful (forecasting, anomaly detection, clustering) using Python libraries.
• Understand how predictive outputs can be operationalized into dashboards.