Mukesh has 2.4 years of experience specializing in data engineering using Apache Spark, Apache Airflow, and Python libraries (NumPy, Pandas, SciPy). He possesses hands-on experience with tools like Jupyter, Databricks, Jira, and Alation. His expertise includes optimizing data pipelines, managing data lakes, and applying in-depth knowledge of ETL processes, advanced analytics, and predictive modeling.
Experience
Data Engineer (Project)
Tata consultancy services
Prepared annual universe estimates for the United States market. Architected schemas and datasets with best way of partitioning to reduce ingestion and execution time by 60%. Used Jira-Board and Gitlab for CI/CD.
Data Engineer / Developer
Tata Consultancy Services
Developed and executed an end-to-end ETL process workflow (DAGS) using Apache-Airflow, Apache-Spark, Pandas, NumPy, and SQL. Used GitLab for version control and CI/CD. Devised workflow and schema for intermediate data-cache and table utilizing dynamic and oops concepts.
Data Engineer (Project)
Tata consultancy services
Devised and created a product to automate Nielsen's weighting technique and prepare universe estimates. Built data pipelines (DAGs) through Apache Airflow with Apache Spark, Python, Pandas, NumPy, and SQL. Worked on AWS Data Lake/S3.
Education
Silicon Institute of Technology
B.Tech.
Electrical and Electronics Engineering
S.C.S Junior College
12th Grade
Science
Licenses & Certifications
Python for Data Science
IBM
Data Analysis Using Python
IBM
Data Visualization Using Python
IBM
Python Project for Data Science
Coursera
Applied Data Science with Python - Level 2
IBM