Preeti Singh

I’m a Senior Data Engineer with 3+ years of experience designing and optimizing scalable ETL/ELT pipelines and cloud-native data platforms. I build analytics-ready datasets by combining Python, SQL, PySpark, Databricks, and modern data warehousing practices.

I’m experienced in Data Warehousing, Delta Lake, Medallion Architecture, Apache Airflow, and data quality frameworks. I’ve improved pipeline performance by up to 70% using Spark optimization and partitioning strategies, while keeping datasets reliable and ready for downstream consumption.

In my recent role at BTSA, ZS Associates, I designed and optimized ETL/ELT pipelines using Databricks, SQL, and PySpark for pharmaceutical, media, and financial datasets. I implemented data quality frameworks and metadata-driven validation logic, reducing pipeline runtime and improving data availability by 70%, and I collaborated closely with business stakeholders to translate requirements into scalable solutions.

Previously at Celebal Technologies, I developed ETL pipelines using SQL, PySpark, Databricks, and Delta Lake with Medallion Architecture, delivering up to 70% performance improvements. On current projects like Roche Integration Hub (ZS) and Mckesson FDP (ZS), I manage complex integration workflows, enhance AWS Glue PySpark jobs, implement monitoring/alerting and orchestration, and deliver transformation logic and data quality frameworks—supported by certifications including Databricks Lakehouse Fundamentals and recognition like the ZS Project Champions Award.