Data Analyst
Smart Ship Hub Digital · Sep 2021 – Present
- Reduced manual reporting effort by 40% by translating stakeholder business requirements into 15+ KPI dashboards in Power BI, enabling real-time performance monitoring and continuous improvement across operations.
- Partnered with product, engineering, and client teams to define KPIs, design analytical use cases, and deliver data-driven recommendations that directly influenced operational decisions.
- Built advanced calculated measures using DAX functions, dynamic parameters, and interactive visuals in Power BI for complex aggregations and time-based trend analysis, supporting solution optimization for key business workflows.
- Designed and implemented Power Query transformations to clean, merge, and reshape large datasets, ensuring high-quality inputs for downstream reporting.
- Worked on RDD creation, transformation and action concepts using PySpark.
- Applied RDD transformations (map, filter, flatMap, reduceByKey, groupByKey) and actions for distributed data cleaning and aggregation.
- Minimized shuffle operations by favouring reduceByKey over groupByKey in aggregation workloads.
- Converted RDDs to DataFrames for Spark SQL querying and reporting-ready output.
- Automated data cleaning and transformation workflows using Python (Pandas, NumPy), improving data accuracy and processing efficiency, enabling faster turnaround on stakeholder reporting.
- Integrated Python scripts with SQL databases to enable real-time data ingestion and analytics workflows, supporting continuous performance tracking across operational datasets.
- Designed and optimized complex SQL queries (CTEs, joins, window functions) on large datasets (10M+ records), improving query performance by up to 30% and reducing reporting latency for business stakeholders.
