Bigdata Consultant - Onsite, OH

On site, 5 days a week, 50 W. Town Street, Columbus, Ohio 43215

Work Hours M-F 8:00AM to 5:00PM EST

The Technical Specialist will be responsible for Medicaid Enterprisev Data Warehouse design, development, implementation, migration, maintenance and operation activities. Works closely with Data Governance and Analytics team. Will be one of the key technical resource for data warehouse projects for various Enterprise Data Warehouse projects and building critical Datamarts, data ingestion to Big Data platform for data analytics and exchange with State and Medicaid partners.

This position is a member of Medicaid ITS and works closely with the Business Intelligence & Data Analytics team.

• Participate in Team activities, Design discussions, Stand up meetings and planning Review with team.
• Perform data analysis, data profiling, data quality and data ingestion in various layers using big data/Hadoop/Hive/Impala queries, PySpark programs and UNIX shell scripts.
• Follow the organization coding standard document, Create mappings, sessions and workflows as per the mapping specification document.
• Perform Gap and impact analysis of ETL and IOP jobs for the new requirement and enhancements.
• Create jobs in Hadoop using SQOOP, PYSPARK and Stream Sets to meet the business user needs.
• Create mockup data, perform Unit testing and capture the result sets against the jobs developed in lower environment.
• Updating the production support Run book, Control M schedule document as per the production release.
• Createand update design documents, provide detail description about workflows after every production release.
• Continuously monitor the production data loads, fix the issues, update the tracker document with the issues, Identify the performance issues.
• Performance tuning long running ETL/ELT jobs by creating partitions, enabling full load and other standard approaches.
• Perform Quality assurance check, Reconciliation post data loads and communicate to vendor for receiving fixed data.
• Participate in ETL/ELT code review and design re-usable frameworks.
• Create Remedy/Service Now tickets to fix production issues, create Support Requests to deploy Database, Hadoop, Hive, Impala, UNIX, ETL/ELT and SAS code to UAT environment.
• Create Remedy/Service Now tickets and/or incidents to trigger Control M jobs for FTP and ETL/ELT jobs on ADHOC, daily, weekly, Monthly and quarterly basis as needed.
• Model and create STAGE / ODS /Data Warehouse Hive and Impala tables as and when needed.
• Create Change requests, workplan, Test results, BCAB checklist documents for the code deployment to production environment and perform the code validation post deployment.
• Work with Hadoop Admin, ETL and SAS admin teams for code deployments and health checks.
• Create re-usable UNIX shell scripts for file archival, file validations and Hadoop workflow looping.
• Create re-usable framework for Audit Balance Control to capture Reconciliation, mapping parameters and variables, serves as single point of reference for workflows.
• Create PySpark programs to ingest historical and incremental data.
• Create SQOOP scripts to ingest historical data from EDW Oracle database to Hadoop IOP, created HIVE tables and Impala views creation scripts for Dimension tables.
• Participate in meetings to continuously upgrade the Functional and technical expertise.

• 8+ years of experience with Big Data, Hadoop on Data Warehousing or Data Integration projects.
• Analysis, Design, development, support and Enhancements of ETL/ELT in data warehouse environment with Cloudera Bigdata Technologies (with a minimum of 7 or more years’ experience in Hadoop, Map Reduce, Sqoop, PySpark, Spark, HDFS, Hive, Impala, Stream Sets, Kudu, Oozie, Hue, Kafka, Yarn, Python, Flume, Zookeeper, Sentry, Cloudera Navigator) along with Oracle SQL/PL-SQL, Unix commands and shell scripting;
• Strong development experience (minimum of 7 or more years) in creating Sqoop scripts, PySpark programs, HDFS commands, HDFS file formats (Parquet, Avro, ORC etc.), Stream Sets pipeline creation, jobs scheduling, hive/impala queries, Unix commands, scripting and shell scripting etc.
• Writing Hadoop/Hive/Impala scripts…