Data Analyst with three years of experience seeking a challenging position to leverage my technical skills and expertise in designing, implementing, and maintaining data infrastructure solutions. Passionate about optimiz…
Data Analyst with three years of experience seeking a challenging position to leverage my technical skills and expertise in designing, implementing, and maintaining data infrastructure solutions. Passionate about optimizing data workflows, improving data quality, and enabling data-driven decision-making.
During my work , I had the opportunity to collaborate with a team of experienced data engineers. I played a key role in designing and optimizing data pipelines, ensuring data quality, and developing scalable solutions. This experience honed my skills in using tools like Python, SQL, and Apache Spark, and taught me the importance of collaborating effectively in a fast-paced environment.
Responsible for the day-to-day management of data, collection, analysis, and summary of information and trends for solution development.
Designed and managed data lakes on AWS, enabling efficient data storage, retrieval, and analytics using services like Amazon S3, Glue, and Athena.
Created, prioritized, and managed Jira issues (stories, tasks, bugs, epics) for effective project tracking and workflow management.
Developed custom Python scripts for specialized data tasks, automating repetitive processes and increasing team productivity.
Skilled in using MySQL performance monitoring tools like MySQL Enterprise Monitor and Performance Schema for proactive optimization.
Developed user-interface that automates manual data process of DSD Duplicate Vendor cleanup to MS Access Database (front end) supported by MS-SQL Server Analysis Model/Database, using tables, VBA forms, and SQL queries.
Spearheaded the automation of investigation reports, metrics, and audit data, transforming manual processes into efficient, data-driven solutions utilizing Tableau and SQL. This resulted in improved accuracy and productivity in the investigation process.
Managed and optimized data warehousing solutions on AWS, including Amazon Redshift, for business intelligence and reporting.
Provided mentorship to a team of 8 individuals in the development of advanced fraud detection protocols, addressing emerging patterns of group and seller behavior. Through effective guidance, the team achieved a 35% improvement in production quality metrics, demonstrating exceptional leadership and team management skills.
Designed data archiving strategies in Python to manage historical data efficiently, reducing storage costs and improving query performance.
Extensive application knowledge in writing complex Structured Query Language in Oracle, SQL Server shop for a given business requirement.
Implemented performance optimization techniques on SQL queries, resulting in a 25% reduction in data retrieval time, demonstrating proficiency in database optimization and performance tuning.
Familiar with NoSQL data storage options within MySQL, such as the JSON data type, to handle semi-structured data.
Prepared ETL Mapping documents & Workflow, thorough Design Documentation for each DataStage Job for Change Detection Load & Control Tie.
Capable of utilizing MongoDB's change streams for real-time data updates and event-driven architectures.
Conducted in-depth analysis of e-commerce data trends using Python, presenting insights through comprehensive reports created using Tableau and MS Excel. Demonstrated expertise in data analysis and reporting, driving informed decision-making for business initiatives.
Designed and implemented views and performed complex data aggregations utilizing SQL.
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