Ramya Sai

Background

About Ramya Sai

Proficient in delivering Business Intelligence solutions using SSIS for data transformation, manipulation, and analysis with SQL.•Implemented Spark RDD transformations and actions for effective business analysis.•Designed Data Quality Framework on Spark (PySpark) for schema validation and data profiling.•Experience working with EMR cluster in AWS and S3 storage.•Leveraged PySpark for manipulating unstructured data and applying text mining.•Created and optimized Hive scripts for data analysts, including UDFs for complex logic.•Designed partitions and replication factors for Kafka topics based on business requirements.•Migrated MapReduce programs into Spark transformations using Spark and Scala.•Automated reports/dashboards in Tableau for monitoring KPIs and improving campaign performance.•Extracted and integrated data from multiple sources using SQL, Python, and ETL for Tableau reporting.•Involved in the complete Big Data flow from data ingestion to processing and analysis in HDFS.•Developed Spark API to import data into HDFS from Teradata and created Hive tables.•Used Sqoop jobs to import data in Avro format from the Oracle database and created Hive tables.•Collected and aggregated log data using Apache Flume and staged data in HDFS for analysis.•Utilized PIG as an ETL tool for transforming, filtering, and aggregating event data.•Developed multiple dashboards in Power BI for analyzing metrics across channels.•Extensively used SQL for ad hoc analysis, recommending features based on user engagement.•Involved in all phases of SDLC, including Requirement Gathering, Design, Analysis, and Testing.•Experienced in working with unstructured and structured data from multiple sources.•Communicated complex technical concepts to technical and non-technical stakeholders, facilitating better understanding and collaboration across teams.•Demonstrated flexibility by successfully adapting to evolving project requirements, new technologies, and changes in the Big Data landscape.•Collaborated seamlessly with cross-functional teams, fostering a positive and collaborative work environment to achieve project goals.•Applied strong problem-solving skills to address challenges in data processing, ETL workflows, and optimization of data pipelines, contributing to efficient project delivery.•Displayed meticulous attention to detail in data analysis, cleansing, and quality assurance processes, ensuring accuracy and completeness in data-driven insights.