Senior Developer & Architect Resume

SUMMARY:

Completely hands - on & expert in Core Java, JEE & Big-data technologies:
Core Java, Multithreading, Hadoop, Cloudera, Hortonworks, Hazelcast, Gemfire, Spring, Hibernate, JMS, EJB, Web Services, Servlets, JSP, XML, XSLT, JDBC, Swings
Expertise in designing low latency, high intensive, multi-threaded, streaming applications using:
Spark: Implemented Spark streams, transformations, actions for Market Risk analytics
Spark-SQL: Experience in fetching data from Hive tables, Parquet & JSON files into DataFrames and efficiently using SQLs to filter and process data in RDDs
HBASE: have used to upsert & read terabytes of transactional & reference data
Sqoop: have used it to transfer Risk data from Oracle into HDFS
Hive: have partitioned the data on Hive using Date for Market Risk. Designed & implemented both internal and external tables in Hive to optimize the performance
Cloudera & Hortonworks: have effectively used these to administrate Hadoop ecosystems
Hazelcast: have used it to achieve extreme performance on medium range pre-calculated data with 100% in-memory solution
MongoDB: have used it to achieve better performance on huge document data
Multi-threads: have used thread executors to parallel Querying, Processing & Staging the huge volume of data for quicker user analytical operations

DATABASES, SERVERS & OTHER TOOLS:

Databases: Oracle 11g and DB2

App servers: Websphere 8.0 and Weblogic 12

Tools: JProfiler, Eclipse, Rational Rose, Enterprise Architect, TLM, MS Project Plan, Visio

Financials: TLM, SWIFT, FpML & ProtoBuf

Domain Experience: Credit Risk, Market Risk, Cash Management, OTC Derivatives (CDS, Interest Rates & Equity), Automated electronic trading (High frequency) development for Forex (FX) market using MACD & RSI algorithms

PROFESSIONAL EXPERIENCE:

Confidential

Senior Developer & Architect

Responsibilities:

I have developed Step framework to load data into HBASE using MapReduce and as well as sequential load after required enrichment is done
Developed Spark scripts to perform various aggravations for Analytical & Reporting systems
Fine-tuned HBASE salting & splitting for better region splits across RegionServers to achieve better performance
Accessed application’s performance and suggested required cluster adjustments

TECHNOLOGIES USED:

Java & JEE: Java 8, HBASE, Phoenix, Spark, Hadoop, Google Protobuf, REST API, Multithreading, Junit

Server& Tools: Linux, Eclipse, Maven, Git, Microsoft Project Plan, JProfiler, Visio

Confidential

Senior Developer & Architect

Responsibilities:

9 frequently used days data are persisted in Spark RDD in-memory with pre-calculated summary & trade levels which resulted in high performance (5 to 10secs)
Rest of historical days are processed on-demand basis using Spark RDDs on Hive/HDFS to get reasonable response time (20 to 30secs) which avoided huge in-memory clusters
Environment configuration: 12 Nodes * 64 GB RAM with 12 * 256 GB Disk space

TECHNOLOGIES USED:

Java & JEE: Java 7, Cloudera CDH 5.7: Hadoop (Spark & Spark-SQL with Hive), Spring Rest API, JDBC, Multithreading, Hazelcast & Junit

Servers: Hadoop Cluster, Weblogic 12, Linux, Oracle 11g

Confidential

Senior Developer & Architect

Responsibilities:

Designed scalable low latency analytical application framework with multi-threaded
Defined interface to communicate between UI and Analytics application and also with external Transfer Pricing, Reference Data & Market data systems
Built API for MongoDB access and setting up MongoDB for 256GB in-memory cache with 4 nodes

TECHNOLOGIES USED:

Java & JEE: Java 7, Spring, Hibernate, MongoDB, EMS (TIBCO), JMS, Multithreading, Gemfire

Deployment: Weblogic 12, Linux with Oracle 11g

Confidential, New York

Technical Architect & Senior Developer

Responsibilities:

Analyzed & Designed common interface to get feeds from various upstream systems; have also coordinated and got this implemented
Designed Gateway with multi-threaded to process different systems incoming feeds, validate, parse, stage in Gemfire and feed to TLM
Fine-tuned the application performance with Gemfire and good number of threads & connections and heap size

TECHNOLOGIES USED:

Java & JEE: Java 6, Spring, Hibernate, Gemfire, JMS, Struts, Multithreading, JUnit

Deployment: Weblogic 9.3, Linux with Oracle 11g

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