Shreyash Kumar

Data Engineer

Bengaluru, Karnataka, India4 yrs 11 mos experience

Highly StableAI ML Practitioner

Key Highlights

Expert in Azure Data Factory and Databricks.
Automated ETL processes, reducing workload by 60%.
Microsoft Certified in Azure fundamentals and data engineering.

Stackforce AI infers this person is a Data Engineer specializing in Azure technologies for the retail industry.

Contact

shreyash.p59@gmail.com LinkedIn

Skills

Core Skills

Azure Data FactorySql

Other Skills

Adobe PhotoshopAndroidAndroid DevelopmentAndroid StudioArtificial Intelligence (AI)Azure Data LakeAzure DatabricksAzure DevOps ServicesBootstrapBusiness RequirementsC (Programming Language)C#C++Cascading Style Sheets (CSS)Chemistry

About

Seasoned professional having around 4+ years of experience. Expertise in Azure Databricks, Azure Data Factory, SQL Server, DevOps and other Azure functionality. Specialized in data migration and transformation. Microsoft Certified in AZ-900, DP-900, DP-203

Experience

4 yrs 11 mos

Total Experience

3 yrs 10 mos

Average Tenure

1 yr 1 mo

Current Experience

Wesco anixter

Data Engineer

May 2025 – Present · 1 yr 1 mo · Bengaluru, Karnataka, India · Hybrid

Azure Data FactoryT-SQLPysparkSpark SQLSQL

Tata consultancy services

2 roles

System Engineer

Promoted

Dec 2021 – Apr 2025 · 3 yrs 4 mos · Bengaluru, Karnataka, India

Role: Azure Data Engineer
Client: ASDA Stores - Large Retailer and Supermarket Chain in UK.
The client is one of the largest retailer and Supermarket Chain in UK. Currently going through a major
transformation and getting separated from its parent organization which includes migration of applications and its
related data.
Developed 20+ high-performance data pipelines using Azure Data Factory to support complex data integration.
Automated ETL processes across billions of rows of data using combination of Azure Data Factory, T-SQL, Pyspark
and Spark SQL which reduced manual workload by 60%.
Wrote optimized advanced SQL queries using CTEs, joins, grouping, aggregation, and nested subqueries to achieve
complex data transformation which increased overall query performance by 40%.
Developed Spark applications using Pyspark and Spark-SQL for data extraction, transformation, and aggregation from
multiple file formats for analyzing the data to uncover insights into the customer usage patterns.
Communicated with team lead, analysts and project managers about business processes and recommend technical
solutions to build data pipelines that drove efficiency KPIs up by 25%.
Worked in a collaborative environment with 20+ other data engineers, analysts, and solution architects.