Portfolio - Dhananchezhiyan T E

Dhananchezhiyan T E

Data Aspirant

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About Me

Hi, I’m Chezhiyan, a data professional transitioning into a full-time Data Engineer role, with nearly 5 years of experience working in the data and analytics space.

I started my career as a QA Engineer, where my work gradually moved into BI and ETL testing. In these roles, I spent most of my time working with SQL and data, validating end-to-end data pipelines, performing source-to-target checks, verifying transformation logic, and ensuring data accuracy for analytics and reporting systems. This experience helped me build a strong foundation in data quality, data warehousing concepts, and analytical thinking.

Over time, I realized that I enjoyed not just validating data, but also understanding how data pipelines are designed and built. This curiosity pushed me to move deeper into Data Engineering. I started learning and working hands-on with modern cloud data platforms, focusing on building real, end-to-end pipelines rather than just theory.

Today, I work with Azure Databricks, ADLS,

1

Data Engineering Project

1

AWS Project

Key Skills

Data Engineering

ETL / ELT Pipelines

Data Modeling

SQL

Python

PySpark

Azure Databricks

Azure Data Lake Storage (ADLS Gen2)

Delta Lake

Microsoft Fabric

Dataflow Gen 2

Onelake

Amazon S3

AWS Glue

AWS Lambda

AWS Athena

Amazon Redshift

Power BI

MySQL

Relational Databases

My Projects

My Experience

ETL & Data Quality Engineer - Lumel Technologies LLP, Chennai

Oct 2024 - Present

Validated end-to-end ETL pipelines supporting analytics and BI use cases by performing source-to-target data reconciliation, transformation logic validation, and row-count checks using SQL and Python, ensuring high data accuracy across reporting datasets.
Tested incremental and historical data loads by validating date-based partitions, CDC logic, and schema consistency, helping maintain reliable daily refreshes for downstream analytics.
Worked closely with data engineering teams to validate datasets built on Azure Databricks, ADLS, Delta Lake, and Microsoft Fabric, identifying data quality issues early and reducing downstream reporting defects.
Supported analytics and BI teams by validating curated datasets consumed by Power BI dashboards, ensuring business metrics and aggregations aligned with defined data models.

System Engineer - Tata Consultancy Services, Chennai

Jan 2021 - Sep 2024

Performed ETL and BI testing for large-scale analytics systems by validating data ingestion, transformations, joins, and aggregations across source, staging, and warehouse layers using complex SQL queries.
Executed data reconciliation and data quality checks (nulls, duplicates, data type mismatches) to ensure consistency between transactional systems and analytical tables.
Validated Slowly Changing Dimension (SCD Type 1 & Type 2) logic and dimensional models, ensuring accurate historical tracking of business entities.
Automated recurring data validation scenarios using Python and SQL scripts, reducing manual testing effort and improving consistency across test cycles.