As a Data Engineer with expertise in both AWS and Azure cloud platforms, I excel in designing and optimizing scalable ETL pipelines to streamline data integration, transformation, and processing. Leveraging AWS services like Redshift, Glue, Lambda, S3, EMR, RDS, and SageMaker, I deliver high-performance data solutions that prioritize scalability, reliability, and operational efficiency. My proficiency extends to Azure tools such as Data Factory, Databricks, Synapse Analytics, and Azure Data Lake, ensuring seamless interoperability across diverse platforms.With a strong command of Python, SQL, Hadoop, PySpark, and Apache Kafka, I have successfully automated data validation using AWS Deequ and enhanced Airflow DAGs, accelerating data pipeline execution and improving overall performance. My hands-on experience with CI/CD tools like Jenkins, Terraform, and GitLab has enabled me to build robust deployment pipelines, incorporating real-time monitoring with Grafana to proactively resolve potential issues.I specialize in data governance and security, implementing compliance measures using AWS IAM, KMS, and Secrets Manager, as well as Azure’s equivalent services. My focus on performance optimization has consistently led to reductions in job runtimes and improved resource utilization, driving impactful results in data processing and transformation across various industries, including healthcare, retail, and finance.Let’s connect to explore how my expertise in AWS, Azure, and big data technologies can transform your data infrastructure, enabling innovation, automation, and operational excellence.
