Data Analyst

Key Responsibilities: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 ReportingTranslate 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.AI/ML ExposureExperience 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.Qualifications:Bachelor’s degree in quantitative field (Statistics, Math, CS, Engineering, etc.) or equivalent.4-5 years of hands-on experience delivering Power BI dashboards in production.Strong Power BI skills: data modeling, DAX, report development and performance optimization.Strong Python skills for data analysis and automation (hands-on experience required).Solid SQL capability.Hands-on Node.js exposure with real delivery experience (APIs / integration support).Strong communication, stakeholder management, and problem-solving skills.IT / enterprise application environment experience is a plus.