Ganesh Halladamal

Who am I?

I'm Ganesh Halladamal, an ETL Engineer and Data Engineering enthusiast passionate about building scalable data pipelines, transforming raw data into meaningful insights, and ensuring high-quality, reliable data for business intelligence. I enjoy working with large datasets and solving complex data integration challenges through efficient ETL workflows.

My expertise includes SQL, Python, PySpark, Pandas, Data Warehousing, ETL Development, Source-to-Target Mapping, Data Validation, Data Reconciliation, and SCD Type 1 & Type 2 implementations. I have hands-on experience with modern data platforms and tools such as Snowflake, Databricks, and Informatica PowerCenter.

I focus on building scalable ETL pipelines, improving data quality, and delivering trusted data that empowers organizations to make informed, data-driven decisions while continuously expanding my knowledge of cloud data technologies.

Hire Me

Tech Stack & Skills

Python
Apache Spark
Pandas
Snowflake
Databricks
Apache Airflow
dbt
Apache Kafka
PostgreSQL
MySQL
MongoDB
Oracle
AWS
Docker
Git
Tableau
Jupyter
HTML
CSS
JavaScript
React
Tailwind CSS
Bootstrap
SASS

Professional Experience

Software Development Engineer

Nighan2 Labs Pvt. Ltd.

March 2025 - Present

Working across data integration and quality assurance, validating end-to-end data flows and automating data quality checks to keep source and target systems consistent.

Key Responsibilities:

  • Analyzed business requirements, functional specs, source-to-target mapping documents, and technical specs to understand data flows, transformation logic, and business rules.
  • Designed and executed functional, regression, integration, and data validation test cases for application and data integration workflows, ensuring accuracy and consistency across systems.
  • Performed SQL-based source-to-target validation and data reconciliation, validating record counts, field-level values, NULLs, duplicates, data types, formats, and mandatory fields.
  • Built and maintained Python automation scripts using Pandas for data profiling, reconciliation, duplicate identification, and data quality validation, reducing manual validation effort.
  • Validated API and database integrations and performed defect investigation by tracing data across application layers, source systems, transformation logic, and target databases.
  • Logged, tracked, and retested defects in JIRA; collaborated with development teams on root-cause analysis and supported regression testing after fixes.
SQLPythonPandasData ValidationETL TestingAPI TestingJIRA

My Expertise

A focused skill set in Data Engineering, ETL development, and building reliable data pipelines that power business decisions.

ETL Pipeline Development

Designing and building robust Extract, Transform, Load pipelines using Informatica PowerCenter, PySpark, and Python for large-scale data integration.

Data Warehousing

Architecting and optimizing data warehouse solutions on Snowflake and Databricks, including dimensional modelling and SCD Type 1 & 2 implementations.

Data Quality & Validation

Implementing data validation frameworks, reconciliation checks, and source-to-target mapping to ensure accurate, trustworthy data for business intelligence.

Cloud Data Platforms

Hands-on experience with cloud-based data platforms including AWS, Snowflake, and Databricks to build scalable and cost-efficient data solutions.

Analytics Engineering

Transforming raw data into clean, analytics-ready datasets using dbt and SQL, enabling teams to build reliable reports and dashboards in Tableau.

SQL & Data Modelling

Expert-level SQL across PostgreSQL, MySQL, Oracle, and Snowflake — writing complex queries, optimising performance, and designing efficient data models.