Adil Shaikh

I am a Senior Data Engineer with 3 years of experience designing, developing, and optimizing scalable data engineering and ETL solutions. My core expertise includes SQL, Python, PySpark, Apache Spark, AWS, Databricks, Snowflake, and Airflow. I have hands-on experience building end-to-end data pipelines, implementing incremental processing, data transformations, data quality checks, workflow orchestration, and performance optimization across large-scale datasets. One of my key achievements was designing and optimizing AWS-based data pipelines for Hindustan Unilever, migrating data from on-premises systems to Amazon S3 and building scalable ETL workflows using AWS Glue, PySpark, Airflow, and Redshift. I also contributed to optimizing AWS and Databricks ETL processes for UnitedHealth Group, achieving a 25% improvement in data accuracy and enabling faster analytical reporting. For my next remote role, I am looking for opportunities as a Senior Data Engineer, Data Engineer, or Cloud Data Engineer where I can work on scalable data platforms, cloud-based ETL pipelines, data processing, analytics infrastructure, and modern data engineering technologies. I am particularly interested in fully remote, long-term roles with collaborative teams where I can contribute independently, solve complex data problems, and continue growing in AWS, Databricks, Spark, and modern data platforms.