- Analyse large-scale time-series, sensor, and operational datasets using Python and PySpark
- Detect trends, anomalies, and performance deviations across distributed data sources
- Quantify data correlations and correction factors to improve measurement accuracy and reliability
- Build and optimize complex SQL and SparkSQL queries to deliver ad-hoc insights
- Design reusable data pipelines and automations for monitoring and data quality checks
- Automate KPI aggregation from APIs, databases, and external systems
- Standardize analytical workflows and data-processing practices across teams
- Curate and prepare datasets for AI, machine learning, and RAG-based applications
- Design and maintain interactive BI dashboards and self-service reporting solutions
- Support root-cause investigations and provide rapid analytical support during operational incidents
PythonSQLMicrosoft Power BI+3 more