Sreehitha Nelluri
Dallas,TX
Summary
Detail-oriented Data Engineer designs, develops, and maintains highly scalable, secure, and reliable data structures. Accustomed to working closely with system architects, software architects, and design analysts to understand business or industry requirements to develop comprehensive data models. Proficient at developing database architectural strategies at the modeling, design, and implementation stages.
Overview
6
6
years of professional experience
Work History
Data Engineer
Walmart
05.2022 - Current
- Designed and implemented real-time data streaming architectures using Apache Kafka and Scala, achieving subsecond latency in data processing and significantly improving the timeliness of business insights
- Developed complex data models and batch processing pipelines with Apache Spark and Hudi on Google Cloud Platform (GCP), enhancing data accuracy and availability for analytics used across business units
- Optimized large-scale data processing operations by refactoring existing batch pipelines, resulting in a 30% reduction in processing times and a 20% cost savings on cloud resources
- Led the migration of legacy data systems to cloud-based solutions involving BigQuery and Dataproc, streamlining data workflows and increasing system scalability to handle over 100 TB of data
- Conducted extensive optimization exercises for existing data pipelines, identifying and eliminating performance bottlenecks, which increased data throughput by over 40%
- Implemented data visualization and reporting solutions with Looker and Tableau, providing actionable insights that drove a 25% improvement in decision-making efficiency across key stakeholders
- Automated data pipeline deployments and operational tasks using Automic, reducing manual intervention by 75% and significantly lowering the risk of human error
- Provided strategic recommendations for data architecture improvements, leveraging GCP services to enhance system resilience and disaster recovery capabilities
- Collaborated with cross-functional teams to ensure seamless integration of analytical tools into the data pipeline, enhancing user accessibility and satisfaction
- Mentored junior data engineers and analysts, promoting best practices in data management and pipeline development, which contributed to a 20% increase in team productivity and a reduction in onboarding times.
Data Science Intern
United Supermarkets
09.2021 - 05.2022
- Streamlining the data feeds from United to Rawls College of Business and preparing business Intelligence reports
- Implemented Machine learning techniques like Market Basket Analysis and Kmeans clustering on huge transaction and customer data." Expert in using BTEQ to code optimal Teradata batch processing scripts for data transformation, aggregation, and load
- Strong coding and debugging abilities for Teradata ETL utilities such as Fast Load, Fast Export, and Multiload for Teradata ETL processing massive volumes (15 million records) of data throughput.
Data Engineering Analyst
Accenture
03.2018 - 06.2021
- Different frameworks are implemented for data ingestion from AWS S3 to Raw layer, transformations have been done to load, control and process the data through the built data pipelines
- Developed SQL scripts in Spark to handle various huge data sets of 20 GB size and tested the performance of jobs
- Managed all jobs through Oozie and their frequencies are set as per the requirement for more than 30 sources(vendors)
- Data was further analyzed using Hive, Excel and involved in development and written various test cases for Testing using Hive/Impala scripts
- Tested and optimized the spark tasks so that the execution time is cut in half
- Analyzed complex data and identified anomalies, trends and risks to provide useful insights to improve internal controls
- Involved in modifying various existing packages, Procedures, functions, triggers in PLSQL according to the new business needs
- Devised high-quality database solutions ranging in size and complexity, increasing productivity and improving data sharing
- Automated report generation tasks by coding in package and saved around 2 hours bandwidth per week
- Drove data analysis, resolving complex business issues and proposing long-term system solutions
- Created optimal technical solutions to user needs through research and in-depth system analysis.
Education
Master of Science - Data Science
Texas Tech University, Rawls College of Business
Lubbock, TX05.2022
Skills
- Spark, Hudi, Hive, Impala, Kafka ,HDFS ,Hadoop Architecture
- Python ,Scala
- MySQL, GSQL, oracle SQL and PLSQL
- Oozie, Automic, Stonebranch
- Tableau ,Looker
- GCP(Google Cloud Platform), AWS (Certified AWS Associate Developer: XH7EFK61PNRQQW9V), OAC (Oracle Analytics Cloud)
Accomplishments
- Won PINNACLE Raising Star Award in Accenture (BCBSM) -2021
- Awarded as the Star Performer in Accenture (BMW UK Apps) -2019
- Reached National level ISTE-Srinivasa Ramanujan Mathematical Competition and placed in merit list -2016
- Won Consolation Prize in the poster presentation on the topic Analog Modulation Techniques conducted under IETE
Timeline
Data Engineer
Walmart
05.2022 - Current
Data Science Intern
United Supermarkets
09.2021 - 05.2022
Data Engineering Analyst
Accenture
03.2018 - 06.2021
Master of Science - Data Science
Texas Tech University, Rawls College of Business