Nilesh User

Senior Data Engineer with 4.5+ years of experience at IBM, specializing in building scalable, cloud-native data platforms and real-time data pipelines. I have hands-on experience designing and developing end-to-end ETL/ELT solutions using Python, SQL, PySpark, Apache Spark, Databricks, Snowflake, and Kafka across AWS and Azure environments.

My work focuses on building reliable, high-performance data systems that support large-scale data processing and analytics. I have strong expertise in batch and streaming architectures, event-driven systems, and delivering low-latency, analytics-ready data for business insights. I’ve worked extensively with Data Lake, Data Warehouse, and Lakehouse architectures, along with data modeling, schema design, and query optimization.

I am passionate about solving complex data engineering challenges, improving pipeline performance, and implementing data quality, validation, and governance frameworks. I also follow DataOps practices, including automation, monitoring, and CI/CD, to ensure scalable and production-ready solutions.

I enjoy working in collaborative, remote environments and am open to global opportunities where I can contribute to building modern data platforms and impactful data-driven solutions.