Data Analyst

Summary

Proficient in data extraction using tools like Sqoop, Pig, Flume, Hive, MapReduce, and HDFS, collaborating with Data Engineering teams for seamless data acquisition.
Skilled in developing user-defined functions (UDFs) in Hive, executing data cleaning and feature engineering tasks using pandas and NumPy in Python.
Experienced in implementing clustering algorithms, advanced techniques for time series data analysis, and presenting insights to managerial teams using Tableau Desktop.
Engages in all stages of research, collaborates closely with operational teams, optimizes database structures, and utilizes Spark SQL API for efficient data processing.
Developed internal visualization platforms, and automated workflows, established REST APIs, and leveraged Python libraries for comprehensive data processing and analysis.
Proficient in troubleshooting, predictive analytics, statistical modeling, data parsing, and generating capacity planning reports.
Expertise in Autosys batch processes, cloud migration (AWS), and utilizing visualization frameworks like Plotly, Dash, and Flask for deeper insights into historical data.

Expectations

learning experience

Employment Preferences

Expected Base Salary

**,000 USD

Expected Hourly Rate

** USD/hr

Academic Degree

Experience

Skills

• Programming Languages
• Python
• SQL
• R
• C#
• Big Data Technologies
• Spark
• Hadoop
• MapReduce
• Hive
• HDFS
• Data Processing Libraries
• Pandas
• NumPy
• Scikit-learn.
• Data Visualization Tools
• Tableau
• Plotly
• Matplotlib
• Ggplot2
• Cloud Platforms
• Azure
• AWS
• Database Management
• MySQL
• PostgreSQL
• Version Control
• Git
• Others
• Unix Shell Scripting
• REST APIs
• Jira
• Excel