SIRISHA VODURU

• More than 11 years of professional IT experience across multiple technologies demonstrating expertise in data engineering, design, and application development.
• Experience in Big data, Data warehousing, data modeling & Automation in building up projects involving Data Ingestion, Transformation, and Processing.
• Excellent programming skills using Scala and Python.
• Experience in data processing with Hadoop Ecosystem tools like HDFS, Hive, Sqoop, Spark with Scala and ETL tools like DataStage9.x and Snowflake with SQL Server, Oracle, Teradata and Unix.
• Worked on the Automation of scripts using Shell scripting & Python. Experience with data manipulation using Python libraries such as Pandas, PySpark, and Numpy.
• Experience in handling large datasets using Partitions, Spark in Memory capabilities, Effective & efficient Joins and Transformations during ingestion process itself.
• Developed RestAPIs using Scala and Akka framework.
• Experience in Machine Learning, Deep Learning and Artificial Intelligence for user analytics.
• Experience in Advanced SQL with RDBMS (SQL Server, Oracle, and Teradata) and developing Hive scripts using Hive UDTF, HQL for data processing and end user analytics.
• Well-versed with importing and exporting data using Sqoop from HDFS to Relational Database Management Systems (RDBMS) and vice-versa.
• Worked on continuous integration and continuous delivery/continuous deployment tools like Team City/Ops logic and GITHUB.
• Worked extensively with AWS technologies like RedShift, S3, Cloud Watch, Athena, Glue, DynamoDB, Lambda, ECS, EKS, EMR, Flink, Kenesis, RDS, Kafka and Athena.
• Involved in the business/client meetings for design, development, requirements discussion and providing solution for complex scenarios.
• Involved in all phases of Unit Testing, SIT, UAT and Support.
• Experience in interacting with Business Users/Stakeholders to analyze the business rules and requirements in Banking and Domains.
• Strong Knowledge on the Spark architecture, Pair RDD’s, Spark DataFrame API including Adaptive Query Execution and profound experience working with UDFs and Spark SQL functions for transforming the raw data to meaningful data for Visualization. Worked explicitly on PySpark and Scala.
• Experienced in developing ETL data pipelines in AWS Glue, Transformed the data using AWS Glue Dynamic Frames with PySpark; Cataloged the transformed data using Crawlers and scheduled the job and crawlers using workflow feature.
• Expertise in Data engineering and Development of various Data warehousing applications and experienced in fact dimensional modeling (Star Schema, Snowflake Schema), Transactional modelling and SCD (Slowly changing Dimensions).
• Well-versed in ingestion of data from different data sources into HDFS using Sqoop and managed sqoop jobs with incremental load to populate HIVE external tables.
• Worked with HIVE data warehouse infrastructure –creating tables, data distribution by implementing partitioning and bucketing, writing and optimizing the HQL queries.
• Experience with different file formats like ORC, Parquet, AVRO, JSON and XML.
• Developed Automation scripts using Shell scripting & Python in building up projects involving Data Ingestion, Transformation and processing.
• Experienced on Advanced SQL (Views/Stored procedures/Indexes) and hands-on experience in handling database issues and connections with SQL such as Oracle, Teradata, SQL Server, MySQL and NoSQL databases such as HBase, Mongo DB, Dynamo DB.
• Instantiated, created, and maintained CI/CD (continuous integration & deployment) pipelines using tools such as Team City/Ops logic and GITHUB/BITBUCKET.
• Expert in designing ETL data flows using creating mapping/workflows from heterogeneous source systems and transforming the data.
• Experience in Creating, Debugging, Scheduling and Monitoring jobs using Orchestration tools like Autosys, Control M and Oozie.
• Worked extensively on agile methodology which involves Iteration planning, Sprint, Retro and backlog planning.
• Experience in interacting with Business Users/Stakeholders to analyze the business rules / requirements and perform source-to- target data mapping. Prepared LLD, Technical Specification documents and providing solution for complex scenarios.
• Efficient Cloud Engineer with years of experience assembling Cloud Infrastructure. Utilizes strong managerial skills by negotiating with vendors and coordinating tasks with other IT members. Implements best practices to create cloud functions, applications and databases.
• Experienced Snowflake data engineer adept at seamlessly integrating Snowflake's cloud-native data warehousing capabilities with AWS services. Proficient in configuring secure data pipelines and optimizing storage solutions, ensuring seamless data access and analysis in the AWS environment.
• Experienced in designing and optimizing data warehousing solutions in Snowflake. Proficient in creating scalable data pipelines, optimizing query performance, and ensuring data integrity within the Snowflake platform.
• Basic knowledge in GCP, Abinitio and Apache Airflow.

• Achieved [Result] by completing [Task] with accuracy and efficiency.
• Collaborated with team of [Number] in the development of [Project name].
• Supervised team of [Number] staff members.
• Achieved [Result] through effectively helping with [Task].
• Achieved [Result] by introducing [Software] for [Type] tasks.

AWS certified Solution Architect - Associate

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