QUALIFICATION SUMMARY

• 8+ years of experience in IT industry, dealing wif and managing complex projects involving multiple stake holders across geographic locations. Designed Data warehousing, Big Data and Business Intelligence Solutions by aligning business requirements and IT strategies, detecting critical deficiencies, and recommending solutions for continuous improvement.
• “Extensive experience in moving Data Warehousing applications from Traditional Database to Big Data and “Health care, Life Insurance, Telecom, Online - Marketing and Publishing Sectors domains”.Knowledge of all major areas of Data Warehousing (Dealing wif Structured & unstructured Data, Data design & Modeling, Reporting and Unit Testing).
• Designed and developed Big Data analytics platform for processing customer viewing preferences and social media comments using Java, Hadoop, Hive and Pig, Spark.
• Hands on experience in developing Applications using Hadoop ecosystem like MapReduce, Hive, Pig, Flume, Sqoop and HBase.
• Excellent understanding of Hadoop architecture and core components such as Name Node, Data Node, Resource Manager, Node Manager and other distributed components in teh Hadoop platform.
• Hands on experience in writing Ad-hoc Queries for moving data from HDFS to HIVE and analyzing teh data using HIVE QL.
• Worked extensively in importing and exporting data using Sqoop from Relational Database Systems (RDBMS) to HDFS.
• Aggregations and analysis done on large set of log data, collection of log data done using custom built Input Adapters and Sqoop.
• Involved in converting Hive/SQL queries into Spark transformations using Python and Scala.
• Extending HIVE and PIG core functionality by using custom User Defined Function's (UDF), User Defined Table-Generating Functions (UDTF) and User Defined Aggregating Functions (UDAF) for Hive and Pig.
• Created Sqoop jobs wif incremental load to populate Hive External tables.
• Good understating of Partitioning, Bucketing, Join optimizations and query optimizations in hive.
• Written custom UDF's in hive and pig to solve certain business requirements.
• Experience in teh successful implementation of ETL solution between an OLTP and OLAP database in support of Decision Support Systems/Business Intelligence wif expertise in all phases of SDLC.
• Familiarity wif teh Hadoop information architecture, design of data ingestion pipeline, data mining and modeling, advanced data processing and machine learning. Experience in optimizing ETL workflows.
• Well versed in configuring teh Hadoop cluster using major Hadoop Distribution like MapR and Cloudera.
• Worked in importing and exporting data from Relational database to HDFS, Hive and HBase using Sqoop.
• Worked on various performance optimizations like using distributed cache for small datasets, Partition, Bucketing in Hive and Map Side joins.
• Worked on teh core and Spark SQL modules of Spark extensively.
• Analyzed large amounts of data sets writing complex Hive queries.Analysis, design, development, testing and Implementation of Business Intelligence solutions using Data Warehouse/Data Mart Design, ETL, OLAP, BI, Client/Server applications. Experience in Data Visualization wif Tableau. Experience wif web scrapping, and statistical tools wif Python.
• Proven Project Management Experience and Supervise large onshore and offshore teams including Mentoring, Appraisal and people development capabilities.
• Design and implement statistical / predictive models and cutting edge algorithms utilizing diverse sources of data to predict demand, risk and price elasticity.
• Strong experience in Dimensional Modeling using Star and Snow Flake Schema, Identifying Facts and Dimensions, Physical and logical data modeling using Erwin and ER-Studio.
• Expertise in working wif relational databases such as Oracle 11g/10g/9i/8x, SQL Server 2008/2005, DB2 8.0/7.0, UDB, MS Access and Teradata.
• Extensive experience in Database Development (Stored Procedures, Functions, Views and Triggers, Complex SQL queries) using SQL Server, TSQL and Oracle PL/SQL.
• Experience wif gathering and creating technical and functional definition and design documents.
• Prior data integration and/or development consulting experience wif a focus on data warehouse architecture, data quality solutions, or master data management solutions.
• Ability to analyze & develop reporting systems architectureand retrieve metadata from Informatica repository and to architect an ETL solution and data conversion strategy.
• Experience in working wif complex datasets to design solutions and providing timely, accurate, documentations for projects.
• Detail oriented wif good communication skills in supporting end-users, work wif client, business users and team members.
• Excellent at identifying, analyzing, and resolve technical issues and performance tuning.
• Work well independently, in groups, and adept at multi-tasking.
• Hands-on experience across all stages of Software Development Life Cycle (SDLC) including business requirement analysis, data mapping, build, unit testing, systems integration and user acceptance testing.

TECHNICAL SKILLS

BIG DATA: Hive, Pig, MapReduce, Spark, Sqoop, Flume, Kafka, Impala, Drill.

ETL TOOLS: Informatica Power center

DATA MODELING: Erwin,Star Schema, Snowflake Schema, Dimension Data Modeling, Fact tables, Dimension tables

OPERATING SYSTEMS: Windows, Unix, Linux

DATABASES & TOOLS: Oracle 9i, Oracle 10g/11g, SQL Server 2000, Teradata 12, Data Studio 4.1.1, HDFS, HBASE, Spark, Big-Data, Hadoop.

BI Tools: Business Objects XI r2/r1/6.5, OBIEE, Tableau, Qlik View.

PROGRAMMING: UNIX Shell Scripting, PL/SQL, Hive, Java, Python.

UTILITY & APPLICATION: Toad, Harvest, PL/SQL Developer, Turnover Process.

TESTING TOOL: Quality Center 9.2, Squids, ALM.

SCHEDULING TOOL: $Universe

PROFESSIONAL EXPERIENCE

DesignationTechnical Lead/Senior Developer

Confidential

Responsibilities:

• Analyze large datasets to provide strategic direction to teh company.
• Perform quantitative analysis of product sales trends to recommend pricing decisions.
• Conduct cost and benefits analysis on new ideas.
• Scrutinize and track customer behavior to identify trends and unmet needs.
• Develop statistical models to forecast inventory and procurement cycles.

Environment: Windows 8, HDFS, MapReduce, Spark, UNIX, Erwin, Tableau, Python.

DesignationTechnical Lead/Senior Developer

Confidential

Responsibilities:

• Working as a Data Warehousing Expert.
• Convert Business requirement into Technical Deliverables (solution Designing) for Off-shore/on-shore teams.
• Technical Lead for Business Intelligence Data warehouse INFORMATICA 9.5
• Build IDQ transformation for data cleansing
• Team Management for Offshore resources.
• Review of mappings developed by other team members. Support to Production team for code Stabilization.

Environment: Windows 8, Informatica Power Center 9.5, DB2, UNIX, $Universe, Mainframe, IDQ..

Hadoop/ETL Developer

Confidential

Responsibilities:

• Worked wif Hadoop Stack - HDFS, MAPReduce, Pig, Hive, HBase, Sqoop.
• Worked in teh transition team which primarily worked on migration of Informatica to Hadoop
• Wrote custom MapReduce programs by writing custom input Formats
• Created Sqoop Jobs wif incremental load to populate Hive external tables
• Handled importing other enterprise data from different data sources into HDFS using Sqoop.
• Responsible for gathering and translating business requirements into detailed, production-leveltechnical specifications, creating robust data models and data analysis features.
• Collaborate wif data architects for data model management and version control.
• Capture technical metadata through data modeling tools.
• Review of mappings developed by other team members. Support to Production team for codeStabilization.
• Designing, reviewing, implementing and optimizing data transformation processes in teh Hadoop
• Analyze large datasets to provide strategic direction to teh company.
• Perform quantitative analysis of product sales trends to recommend pricing decisions.
• Conduct cost and benefits analysis on new ideas.
• Scrutinize and track customer behavior to identify trends and unmet needs.
• Develop statistical models to forecast inventory and procurement cycles.