Akhil Mule Email & Phone Number

As a highly skilled Data Analyst with expertise in Azure, Python, SQL, and data visualization tools, I have a proven track record of optimizing data analytics workflows and delivering actionable insights that drive strategic business decisions. My experience spans various industries, where I’ve successfully integrated Azure SQL Databases with analytics tools, developed and maintained data pipelines using Azure Data Factory, and designed SQL queries for efficient ETL processes. I leverage Python for advanced data analysis and automation, creating scripts that enhance data quality and streamline operations. My data visualization work includes designing interactive Power BI dashboards, developing complex Excel models, and utilizing tools like SAS and Google Data Studio to present comprehensive findings to stakeholders. Additionally, I have experience with the Hadoop ecosystem, using HDFS, MapReduce, and Hive to process large datasets. My expertise also extends to developing automated ETL processes with Oracle PL/SQL, integrating data from diverse sources, and ensuring the accuracy and reliability of data across multiple platforms. I’m passionate about turning complex data into actionable business intelligence, and I thrive in environments where I can collaborate with stakeholders to define data requirements and deliver tailored solutions that meet organizational goals.

As a Senior Data Analyst at Raymond James Financial from May 2019 to June 2021, I spearheaded the development and maintenance of robust data pipelines utilizing AWS technologies such as S3, Lambda, Glue, and EMR, automating data ingestion and processing workflows that significantly enhanced data retrieval and reporting capabilities. My role involved implementing SQL queries to extract, manipulate, and analyze large datasets, ensuring accurate and timely reporting across cross-functional teams. I conducted advanced statistical analysis and hypothesis testing using Python libraries like SciPy, and deployed R Shiny applications for interactive data exploration and visualization.During my tenure, I was responsible for maintaining MySQL, PostgreSQL, and Oracle databases, performing routine tasks such as backups, updates, and security audits to ensure high performance, availability, and data security. I also optimized SQL queries and developed stored procedures for efficient data extraction and transformation, and leveraged SAS Base and SAS Access for data integration, cleaning, and transformation from diverse sources. My expertise in the Hadoop ecosystem allowed me to configure HDFS and YARN components, integrating Hadoop with Excel for detailed data analysis and visualization.I was also instrumental in developing interactive Power BI dashboards and reports, creating custom visuals and utilizing Power Query for advanced data transformation tasks, providing real-time insights into key business metrics that enhanced decision-making processes. My proficiency in managing Jupyter Notebook environments using platforms like Jupyter Hub facilitated collaborative and scalable data analysis, while my experience with Google Analytics enabled comprehensive tracking and reporting of website performance, user behavior, and conversion metrics.

During my tenure at Max Healthcare, New Delhi, from August 2017 to January 2019 as a Data Analyst, I played a crucial role in enhancing data-driven decision-making processes by leveraging advanced data management and analytics tools. I developed and managed robust data pipelines in Azure Data Factory, ensuring seamless data ingestion, transformation, and integration with Azure SQL Database. My work involved utilizing Python and R for complex data analysis, predictive modeling, and generating actionable insights from extensive datasets.I optimized SQL queries to improve data extraction, cleaning, and analysis from multiple sources, including Azure SQL, which significantly enhanced reporting accuracy and efficiency. Additionally, I developed comprehensive Excel dashboards and reports, integrating data from various sources to provide clear and effective visualizations for stakeholders. In my role, I managed and optimized Hadoop clusters, ensuring high performance and reliability in processing and storing big data across distributed systems. I also conducted data migration and integration projects between PostgreSQL and Oracle, developed and maintained MySQL databases, and implemented ETL pipelines using Azure Data Factory to integrate data into Azure Data Lake.Moreover, I developed and maintained SAS macros to automate repetitive tasks, streamlined data processing workflows, and automated data processing tasks using Excel VBA macros, reducing manual effort and increasing efficiency. Additionally, I integrated Tableau with various data sources, including SQL databases and cloud platforms, to streamline data analysis. I also utilized SAS statistical procedures for in-depth data analysis, enhancing the accuracy of predictive models, and conducted interactive data analysis using Jupyter Notebook with Python libraries such as Pandas and Matplotlib.

At Bharti AXA Life Insurance, I served as a Data Analyst, where I was instrumental in optimizing data storage, processing, and analysis to drive business insights and decision-making. I leveraged AWS services, including AWS S3 and Redshift, to streamline data storage and querying processes. By utilizing Python for data processing and R for advanced statistical analysis, I was able to generate actionable insights that supported strategic business decisions. I designed and implemented SQL queries for efficient data extraction and manipulation, integrating the results with Python scripts and R models. My role involved developing and optimizing complex SQL queries and procedures in MySQL, PostgreSQL, and Oracle to ensure high-performance data retrieval and accurate reporting.I designed scalable data processing workflows using Hadoop MapReduce to handle and analyze large-scale datasets and maintained data pipelines with tools like Pig and Sqoop for automated data transformation. I also managed data quality metrics using AWS S3 and executed data validation and cleansing tasks with AWS EMR to ensure the integrity of the data. In addition to technical responsibilities, I created detailed documentation and reports in MS Word, summarizing analytical findings and methodologies. I implemented conditional formatting rules in Excel to enhance data accuracy and developed custom Excel add-ins using VBA to automate repetitive tasks, extending Excel’s functionality for specialized reporting needs.I developed and maintained Python scripts for automating ETL processes to enhance data accuracy and operational efficiency. My work included optimizing SQL queries and Tableau dashboards for efficient data retrieval and utilizing Python libraries such as Pandas, NumPy, and Matplotlib to perform complex data analysis.