Itishree N.

Data Engineer

Bengaluru, Karnataka, India15 yrs 9 mos experience

Most Likely To SwitchHighly Stable

Key Highlights

Expert in Big Data technologies and cloud computing.
Proven track record in data migration and ETL processes.
Strong experience in developing data frameworks and applications.

Stackforce AI infers this person is a Big Data Engineer with expertise in cloud migration and data management.

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Skills

Core Skills

Data EngineeringBig DataData Migration

Other Skills

HanaSinglestoreHadoopHiveOozieAutosysETLSQLSqoopSnowflakeMainframeBasics of UnixShell ScriptingApache PigGit

About

Software developer with hands on experience in cloud computing, big data and Hadoop technologies. Utilizing my capabilities to achieve personal and professional growth while, working in close consonance with the goal of the organization, adding value to the organization, imbibing the work culture in return.

Experience

15 yrs 9 mos

Total Experience

5 yrs 3 mos

Average Tenure

7 yrs

Current Experience

Apple

2 roles

Senior Data Engineer

Oct 2025 – Present · 7 mos

HanaSinglestoreData Engineering

Data Engineer

May 2019 – Oct 2025 · 6 yrs 5 mos

Bank of america

2 roles

Analys I Apps Prog

Feb 2017 – May 2019 · 2 yrs 3 mos

Senior Software Engineer

Dec 2014 – Feb 2017 · 2 yrs 2 mos

Infosys

2 roles

Senior Software Engineer

Promoted

Jan 2013 – Dec 2014 · 1 yr 11 mos

Hadoop-EDW Semantic Framework Development :
A Generic Semantic framework was developed for carrying out all the Semantic processes. The Hive queries needed to be formed and configured as Design time Metadata for the framework. The oozie flow executes the queries sequentially/parallel. The framework executed the queries automatically after being started by the autosys job. The framework had the capability for statistics collection. It also used to update the run-time metadata. The key challenges faced here is to implement the update functionality which was present in TD.

Software Engineer

Jul 2010 – Dec 2012 · 2 yrs 5 mos

Hadoop EDW Pilot phase
Hadoop EDW Pilot phase is a cloud migration project developed using java that uses Hadoop as File system and Hive. Data of various applications is loaded into the EDW using the ETL process. POC was done to migrate EDW data from Teradata to Hadoop. Data from Teradata tables is migrated to Hive tables. Hive QL is used to run map-reduce jobs on HDFS to load the data from flat files to the core tables. The data generated by various Applications across all regions is finally aggregated as an end result. In addition to faster processing and reduced cost storage, it also migrates existing data from Teradata to Hadoop.
Data management Phase 3
DM3(Data management Phase 3) is a Data migration project to move all the data from different DB servers to Common data source and involved in data acquisition, data validation and data distribution. An application was developed for getting the data from the source(CAISO site) and load in the Central Data Repository(CDS in ORACLE). Here, after fetching the data from source, the background processing like inserts, updates or deletes are performed in Hadoop through Hive queries. Finally the data was exported to SQL using SQOOP.