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.
<p>Designed, developed, and maintained ETL processes to ensure efficient data extraction, transformation, and loading into data warehouses.<br>
Collaborated with cross-functional teams to analyze business requirements and implement data solutions that enhanced operational efficiency.<br>
Optimized data pipelines resulting in a 20% reduction in processing time, improving overall system performance.<br>
Conducted troubleshooting and performance tuning to address bottlenecks and ensure data integrity.<br>
Utilized PySpark to distribute data processing on large streaming datasets to improve ingestion and processing speed of data by 87%.<br>
Automated ETL processes across millions of rows of data which reduced manual workload by 32% on a monthly basis.<br>
Dimensionally modeled sales data using star schema (fact and dimension tables) and built a PowerBI dashboard on it.<br>
Increased the efficiency of data pipelines that processed over 100 GB of data daily.</p>
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