Sandhya Gandla

• Experienced Data Engineer with 5+ years in designing scalable data pipelines using AWS, Azure, GCP, Spark, and Hadoop, driving data-driven insights and leveraging innovative technologies to solve complex challenges. • Expertise in Big Data technologies including Hadoop, Apache Spark, Databricks, and Snowflake for managing and analysing large datasets with optimized workflows. • Proficient in Spark Core, Spark SQL, and Spark Streaming, with advanced performance tuning to enhance efficiency in real-time and batch data transformations. • Developed ETL pipelines using AWS Glue, Azure Data Factory, Google Cloud Dataflow, Informatica, and Talend for seamless data integration and transformation. • Strong experience with SQL and NoSQL databases like Oracle, SQL Server, MySQL, Cassandra, Teradata, PostgreSQL, Amazon Redshift, HBase, and MongoDB for optimized data handling. • Skilled in workflow automation and orchestration using Apache Airflow, Oozie, and Azkaban, creating DAGs for real-time scheduling and monitoring. • Extensive CI/CD implementation using Jenkins, Kubernetes, and Terraform, ensuring smooth deployment of scalable data pipelines across cloud environments. • Strong proficiency in Python, Scala, and Java, applying them in distributed computing, machine learning, and big data processing solutions. • Experience managing cloud services such as AWS S3, Redshift, EMR, Kinesis, Lambda, Azure Blob Storage, Synapse Analytics, Databricks, GCP Big Query, and Cloud Storage. • Skilled in data modelling and governance, utilizing Erwin Data Modeler to create star and snowflake schemas for performance-optimized data structures. • Expertise in data visualization tools like Tableau, Power BI, Looker, and Quick Sight, developing dashboards for actionable insights and business intelligence. • Collaborated with cross-functional teams to optimize data workflows, enhance business analytics, and deliver scalable, enterprise-wide data solutions.