Aspiring Data Analyst with a background 5+ years of experience of building ETL data pipelines, collecting, sorting and analyzing data. Skilled at data analytics, pre-processing, visualization, automation, statistical mod…
Aspiring Data Analyst with a background 5+ years of experience of building ETL data pipelines, collecting, sorting and analyzing data. Skilled at data analytics, pre-processing, visualization, automation, statistical modeling using Python, SQL. Passionate to drive meaning out of data using programming tools, deep logic and a statistics driven mindset, to drive long-term value, efficiency and increased profitability. Skilled at establishing, programming for KPI metrics.
Aspiring Data Analyst with a background 5+ years of experience of building ETL data pipelines, collecting, sorting and analyzing data. Skilled at data analytics, pre-processing, visualization, automation, statistical modeling using Python, SQL. Passionate to drive meaning out of data using programming tools, deep logic and a statistics driven mindset, to drive long-term value, efficiency and increased profitability. Skilled at establishing, programming for KPI metrics.
Designed, developed, and maintained ETL processes to ensure efficient data extraction, transformation, and loading into data warehouses.
Collaborated with cross-functional teams to analyze business requirements and implement data solutions that enhanced operational efficiency.
Optimized data pipelines resulting in a 20% reduction in processing time, improving overall system performance.
Conducted troubleshooting and performance tuning to address bottlenecks and ensure data integrity.
Utilized PySpark to distribute data processing on large streaming datasets to improve ingestion and processing speed of data by 87%.
Automated ETL processes across millions of rows of data which reduced manual workload by 32% on a monthly basis.
Dimensionally modeled sales data using star schema (fact and dimension tables) and built a PowerBI dashboard on it.
Increased the efficiency of data pipelines that processed over 100 GB of data daily.
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