Big Data Hadoop Developer Resume
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SUMMARY
- Big Data Hadoop Developer with over 3 years hands - on technical experience in the Healthcare industry.
- Extensive ETL experience moving data from relational databases into on-prem Data Lakes and cloud data warehouse like Snowflake.
- Proficiency with SQL to curate raw data and do analytics on complex data.
- Ability to translate business requirement in technical specifications.
- Successful in delivering solutions in both technological and corporate environments.
TECHNICAL SKILLS
- Ambari, HDFS, MapReduce, Sqoop, Pig, Hive, HiveQL, HBase
- Spark SQL
- Oracle, SQL Server
- Snowflake - Cloud Computing
- Epic Chronicles
- Clarity Workbench
- Clarity Reporting
- Clarity Data Warehouse (BI/Analytical Reporting)
PROFESSIONAL EXPERIENCE
Big Data Hadoop Developer
Confidential
Responsibilities:
- Manage daily ETL batch jobs to migrate data from EMR applications (EPIC) into Hive (Raw Zone).
- Manage daily ETL batch jobs to migrate data from EMR applications (EPIC) into data lake.
- Generate adhoc reports (BAU’s) from Hive to quickly support various business analytical needs.
- Troubleshoot potential technical issues from batch jobs.
- Support daily jobs that extract flat files from Chronicles (Cache) and loads into Clarity (Oracle) to support enterprise reporting.
- Help develop new strategies to capture, store and analyze data for increased access and lower costs.
- Analyze datasets using Hive, and Sqoop to recommend business improvements.
- Import data from Oracle to HDFS, using Sqoop to load data.
- Tune performance of legacy Hive queries to improve data processing and retrieving.
Data Analyst
Confidential
Responsibilities:
- Helped developed ETL batch jobs that migrate data from AllScripts into Oracle database
- Developed various business reports using SQL to generate CSV files
- Analyze datasets in Hadoop using Hive QL, Impala, Spark SQL
- Developed Sqoop scripts to extract data from Oracle into Hive.
- Develop complex data models to support analytical reporting.
- Develop data models for storing EMR records such as patient treatment plans, medications and recovery tracking.