Nalin Raj

Data Engineer with 3+ years of experience designing, optimising, and supporting production-grade ETL/ELT pipelines and warehouse transformation layers. Architected and maintained 15+ Airflow-orchestrated workflows processing 2–3 million records daily into Snowflake environments. Improved pipeline performance by up to 30% through SQL optimisation and transformation redesign. Experienced in dimensional modelling, validation frameworks, and production support within Agile delivery teams.

Data Engineer - Softwire - Leicester, UK

(2024-01)

Environment: Python, SQL, Snowflake, Apache Airflow, Power BI

• Architected and maintained 15+ production Airflow DAGs processing ~2–3 million records daily.
• Engineered transformation layers across 25+ warehouse tables supporting 10+ dashboards.
• Optimised SQL execution plans reducing pipeline runtime by ~30%.
• Automated ingestion and reconciliation workflows reducing manual effort by ~40%.
• Implemented validation controls ensuring data accuracy prior to downstream publication.
• Introduced monitoring and retry mechanisms reducing failure resolution time by ~35%.
• Led root cause analysis on production incidents improving system stability.

Data Engineer - Wipro

(2020-01 - 2022-12)

Environment: SQL, Python, MSSQL, Snowflake (exposure), AWS (exposure)

• Developed enterprise ETL workflows supporting 8+ reporting teams.
• Designed and enhanced 20+ fact and dimension tables aligned with Star/Snowflake modelling standards.
• Improved nightly batch performance by 25–35% through indexing and SQL optimisation.
• Refactored transformation logic to standardise structured data flows.
• Automated recurring ETL processes reducing manual intervention by ~30%.
• Evaluated cloud ETL workloads to inform scalability and modernisation decisions.

MSc - Advanced Computer Science - University of Leicester (2023-01 - 2024-12)

BTech - Computer Science - Nitte Meenakshi Institute of Technology (2018-01 - 2022-12)