LASYA NAMINENI

Email: adlg4u@r.postjobfree.com, Phone:732-***-****.

An enthusiastic data engineer seeking a position in progressive organization which can expand my knowledge and provide me exciting opportunities to utilize my skills and qualification. Technical Skills:

− Big data: Hadoop, Spark, Kafka

− Analytics: Python/Pandas/NumPy/Scikit-learn, Spark MLlib, Pyspark, pyspark mllib,koalas, Impala.

− Cloud: Amazon Lex, Kinesis, Quick sight, Glue, API Gateway, Lambda, Cloud Watch, Azure Hd insight

− Database: Oracle, Cassandra, Mongo, Athena,SQL, HIVE

− Operating Systems: Windows, Linux, and Mac OS.

− Languages /Web: Python, Java, R, Scala, C++, PHP, HTML, CSS, Javascript, JQuery, Node.js.

− Visualization: Tableau, Microsoft Power BI

Experience:

Cognizant Technology Solutions - Data Engineer (Aug 2019 - Present)

− Worked on Purdue leaperex project where I worked with data scientists to compare on-demand, fixed route bus approach. Did preprocessing on raw leaperex data, Built an ETL pipepline using spark to bring in hourly weather data parallely from dark sky api.

− Worked on building ETL pipeline for Warranty Recovery Project where we migrated exiting solution from jmp to datalake. Reduced the processing time of the original solution from 28 hrs to 1 hrs using spark. Used graphframes to connect the suppliers to the parts. The pipelines loads results to SQL upon which power bi is connected.

− Developed and productionalized ETL pipelines using databricks, delta lake, hive,SQL. Scheduled the jobs using appworx.

− Worked on upgrading the data pipelines running in azure datalake gen1 to gen2 .

− Worked on developing a streaming solution that runs every 15min, which acts as input to the an ml model. Created an ml api end point to serve the results of the model. Developed this solution in pyspark.

− Worked on developing an API in node JS to get http post, get requests from users and route it to ml endpoint that is created on databricks.

Technologies: Spark,Azure Data lake, Appworx, spark scala, Hive, power bi, sql Intellinum Analytics Inc (Data Engineer) (May 2019 – Jul 2019)

− Performed ETL tasks using Spark to extract and transform TBs of RTB(Real-time Bidding) bids stream data to generate features for the Click-through-rate prediction models used in the DSP bidder. Filtered Bot traffic from RTB bid stream data. Was able to find fraud user_id based on frequency of IP address, Bundle_id used. Filtered bots based on Time analysis of the IP and budle_id used by an user_id. NYU Projects (MS Computer Science) (Aug 2017-May 2019)

− Click-Stream Analysis for Online Retail Stores: Used Amazon Kinesis stream to get the data generated from a lambda function and Kinesis Analytics to sessionize it. AWS Data Glue is used to crawl data from S3 and update the Amazon Athena tables which were visualized in Amazon Quicksight.

− Log Analysis with spark: Developed a scalable application that analyzes the log data to compute statistical information. I used spark streaming for real monitoring of data and used Kafka to import data. The data is streamed into jupyter notebook where the data is analyzed using pyspark to spot DDos attacks.

− Dining Concierge Service: Implemented a chatbot that gives you restaurant suggestions given a set of preferences through conversation. This is a serverless, micro-service driven web application. The frontend is hosted in AWS S3, authentication setup using Cognito, chat bot using Amazon Lex . Certifications:

− Neo4j Certified Professional (Certification authority: Neo4j, License no: 16834170)

− AWS Certified Cloud Practitioner.

− Az 900 certified

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