
Akash Anand
Development
Karnataka, India
Skills
Data Engineering
About
AKASH ANAND's skills align with System Developers and Analysts (Information and Communication Technology). AKASH also has skills associated with Database Specialists (Information and Communication Technology). AKASH ANAND appears to be a low-to-mid level candidate, with 3 years of experience.
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Work Experience
Data Engineer
TCS
August 2021 - Present
- Orchestrated end-to-end Azure Data Factory (ADF) pipelines, accelerating SLG Report generation with a 30% reduction in data processing time. Implemented efficient data processing techniques, such as broadcast join and strategic file format selection (Parquet for reading data and CSV for writing final feed), resulting in a 40% reduction in report generation time. Collaborated cross-functionally to identify and rectify data anomalies, applying PySpark transformations to achieve a 70% accuracy improvement in data quality. Implementing Data Modeling techniques, specifically focusing on creating and managing SCD Type 2 structures Orchestrated the creation of an architectural design in collaboration with the Project Manager, aligning with the business specifications Supervised the Impact Analysis of changes in downstream systems, ensuring a smooth transition to Data Warehousing and Reporting Systems. Extracted data from the Oracle Database and generated mappings, workflows, and transformations to establish efficient pipelines for data transfer and increasing the sales by 27%. Developed and optimized SQL scripts to enhance the performance of workflows, maximizing efficiency in data processing and enhancing the performance by 30% Implemented Snowflake's Time Travel function in SQL queries, resulting in a 25% reduction in data analysis time, to scrutinize new data against historical records, driving insightful comparisons
Software Engineer Intern
TCS
March 2021 - May 2021
- Sperheaded the cleaning and transformation of over 1 million sales records using PySpark, ensuring impeccable data quality and integrity. Leveraged cutting-edge PySpark and Spark SQL for a thorough analysis of sales data, extracting valuable and actionable insights. Improved data accuracy by 25% through precise execution of data cleaning tasks, addressing missing values and outliers. Implemented broadcast join in PySpark, boosting data processing efficiency by 20%.