senior software engineer
Resume:
Sriraj K adimisetty
Lead S oftware E ngineer
Alpharetta, G A
ac2b2q@r.postjobfree.com
SUMMARY
● Senior Developer with 7+ years of continuous software development in developing solutions and also have v ery s trong a ptitude t owards l earning n ew t echnologies.
● “Go to Guy” when a solution is needed. Able to analyze business requirements and formulate creative design a nd t echnical a pproaches i n b oth i ndividual a nd t eam s ettings.
● Expert k nowledge i n M icroservices d omain(Spring S tack), H adoop/HDFS, S treaming A rchitectures.
● Expertise i n S ervice O riented A rchitecture a nd O bject O riented D esign.
● Well versed and hands on experience with Event Driven, Event Sourcing and Message Driven Architectures.
● Good e xposure o n L INUX e nvironment a nd a lso c ontainer b ased s olutions s uch a s D ocker
● Worked o n v arious S pring f rameworks.
WORK E XPERIENCE
Lead S oftware E ngineer
Total S ystems ( TSYS A lpharetta, G A
Sep 2 016 – C urrent
TSYS is a financial based vendor service for different financial organizations across the globe. As part of modernization effort they were looking for options to go with leading edge and open-source stack for both compute and storage along with operational and analytical use-cases, key consideration in the effort was cost saving w ithout c ompromise o n t he p erformance. MAPR is used as the Hadoop platform. Datalake project started as a operational data store for all client API’s along with analytical support for several reporting framework teams with no purging of data in parallel to current mainframe environment (current client facing API’s). Built a NRT (near real time) pipeline for data transfer from IMS(Source of truth) to Datalake with PCI constraints(Tokenization service) taken into consideration. Architected entire pipeline with event sourcing and CQRS approach and ensured not to get into 2 phase commits. In the process used CDC for capturing the logs on IMS source, Kafka/MaprStreams as the EventSource as it provides high performance out of the box with minimal configuration along with pub-sub mechanism and built real time indexing to Hbase/MaprDB(viewing layer for API’s) on top of Spark Streaming(provides microbatching out of the box) as Hbase performs better writes in batch mode vs single puts. Flink is used for ingesting data to HDFS (impressed by the bucket sink feature and auto memory management w ith v ery m inimal t uning).
Also as part of the above effort, used avro format as the data interchange all along the pipeline and used NIFI wherever necessary to minimize the coding and use several built in processors out of the box with its ability for data provenance features. Kafka Streams is also used in the pipeline process for transformations because of its ability to process the records in order within a partition inside the Kafka topic. All the application metrics are indexed t o I nfluxDB a nd u sed G rafana f or m etrics d ata v isualization. Architected and involved in developing several microservices for the operational data pipeline(viewing layer in CQRS approach) on top of Spring boot to expose Restful APIs with Spring MVC for B2B and B2C applications. Used Spring security for security configurations and designed custom Oauth2 implementation, used HMAC for B2B c alls.
Designed a c ustom J ava l ibrary o n t op o f H base f or D ata A ccess C alls. U sed I batis f or O RM. Also involved in designing Notification service for the Enterprise applications to push notifications like SMS/ Email f or t he c ustomers o n t op o f N IFI. Involved in several talks along with devops to design a container based platform on top of docker swarm for microservices with custom server side discovery pattern. Used Mapr PACC client for building several stateful containers o n M APR p latform.
Tech used: Hadoop, Spark Streaming, Flink, NIFI, Hbase, MaprDB, HBaseSolrIndexer, Spring stack, Apache Kafka, MaprStreams, Scala, SQ DATA CDC, ActiveMQ, Docker, MaprStreams, MaprDB (Binary and Json), Kerberos integration, Spring Boot, Spring Framework, HAPROXY, OracleDB, Docker Swarm, Oauth2, Hmac, Jenkins, G it, E LK, N exus.
Senior S oftware E ngineer
State F arm I nsurance, B loomington, I L
Feb 2 012 – A ug 2 016
Legacy Modernization: This is a search based application where there was need to identify the owner for the mainframe programs. This was an enterprise crowdsourcing effort and needed to ingest data into HBase and through morphlines needed to map the HBase table to Solr index which was the source for search. The entire application was developed in a record time with zero issues. Top level leadership were appreciative of this effort.
Tech u sed : H Base, M orphlines, S olr, A ngularJS, S pringMVC, H base L ily I ndexer Customer360 : This was another search based application where multiple indexes data was to be searched to give a holistic dashboard view of the customers data. There was a need to source in data from multiple systems and represent the data from the multisource single Solr index. The dynamic nature of the UI will query the S olr i ndex i n d ifferent f orms a nd p aint t he d ata w ith m ulti-facets. Tech U sed: H Base, S olr, M orphlines, A ngularJS Life Journal: This app reads data from HDFS flat files and writes into HBase table. The data was almost 4TB in size and was read through Reduced Side join(Mapreduce program). The table had 9 million rows with 225000 columns m ake i t s calable w ith p roper k ey d esign f or a nd s plitting t he t able k ey s plits t o a void h ot s potting. TechUsed: H Base, H DFS, M apreduce, S pring B atch, S pring R est, S pring M VC Electronic-Signature: Involved in Architecture and Development for exposing restful API across Enterprise for several LOB to use electronic signature feature. Designed several mule flows for orchestration and used RabbitMq f or m essage d riven s ervices. T hese A PIs a re e ventually c onsistent s ervices. TechUsed: S pring s tack, P ostgresql, R iak, M ule. Mule Custom Adapters: As part of this effort, designed enterprise wide service discovery pattern in mule to discover services on client calls and also maintain versioning and configured custom lane concept for microservice consumption/testing across environments so several teams can work independently without any dependency all along in integration with WSRR. Also as we decided on the architecture to consume queues only through mule flows, there is lot of confusion on handling error scenarios and DLQ limit, so we designed a layer t o f lush t he m essages t o R IAK a nd c onsumer t he m essages b ack f rom R IAK o n s ervice a vailability TechUsed: S pring s tack, M ule, W SRR, R IAK JRF: Designed in refactoring monolithic request framework to loosely coupled web services. This application is responsible for product catalog and business rules and also built on write behind cache/ read through cache to i mprove p erformance. U sed G emfire a s d istributed c aching f ramework. TechUsed: S pring s tack, M ule, R iak, P ostgresql, G emfire Health Monitor: Involved in developing a custom metrics platform for all the services available across the enterprise to monitor several metrics. This application itself has several components underneath with Splunk being d ata s ource a nd a gain u sed C aching a s t he d ata c ollector f or t he U I. TechUsed: S pring s tack, M ule, R iak, P ostgres, A ngularJs, G emfire, S plunk Software D eveloper
Liberty M utual I nsurance, I ndianapolis
May 2 010 – J an 2 012
Involved i n d eveloping a f ull s tack m onolithic j ava a pplication f or q uote a nd r ate e ngines o n c ommercial L OB. Environment: Java, J2EE, Spring, Struts, Servlets, JSP, JSP Tag Libraries, Javascript Libraries, HTML, JDBC, JUNIT, A NT, T omcat, M ySQL, S VN, H udson, L inux, J query, J SON, M aven, E asyMock. EDUCATION
Bachelor's: V isvesvaraya T echnological U niversity, B angalore. 2 003 – 2 007 Masters i n E lectrical E ngineering: W right S tate U niversity, O H. 2 008 – 2 010 OTHER TECHNOLOGY STACK APART FROM
ABOVE
NodeJS, Grafana, InfluxDB, GIT, JENKINS, NEXUS, JFROG, MAVEN, DropWizard Metric Integration, MONGODB, ELK s tack, A WS e tc.
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