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.
Tech Stack & Skills
Professional Experience
Software Development Engineer
Nighan2 Labs Pvt. Ltd.
Currently working as a Software Development Engineer, focusing on building scalable web applications and implementing modern development practices.
Key Responsibilities:
- Developing and maintaining full-stack web applications
- Implementing responsive UI components with React and Next.js
- Building RESTful APIs and integrating with databases
- Collaborating with cross-functional teams in agile environment
- Writing clean, maintainable, and well-documented code
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.