Description

Job Description:

  • At least 4+ years of relevant experience in DataStage Admin, Development and CDC.
  • At least 2 years of recent hands-on experience in IBM Data Stage using v11.x ETL tool and rest in other ETL tools.
  • Expertise in Data Warehousing ETL Tool DataStage using Components like DataStage Designer, DataStage Director and DataStage Operations Console.
  • Efficient in all phases of the development lifecycle, coherent with Data Cleansing, Data Conversion, Performance Tuning and System Testing.
  • Expertise in designing DataStage Parallel Jobs, Job Sequencing, Creating Parameter Sets, Environment Variables and Creating Parallel Routines, Data Cleansing and Writing Transformation expressions to derive values and remove unwanted data.
  • Efficient in identifying and finalizing the various source file formats and frequencies from different source systems.
  • In depth experience in troubleshooting of Datastage jobs and addressing issues like performance tuning.
  • Expert level proficiency in UNIX skills.
  • Experienced in automation of the jobs using Unix scripts.
  • Experience in developing reusable Unix Jobs/components.
  • Strong understanding of Data warehousing concepts, dimensional Star Schema and Snowflakes Schema methodology.
  • Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using Snowflake Cloud Data Warehouse as well as SQL and Azure ‘big data’ technologies.
  • Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  • 4+years of experience in database technologies like DB2, Oracle, TERADATA, Hive and HBase.
  • Very efficient in developing SQL queries and debugging complex SQL queries.
  • Expert level SQL tuning skills in any of the RDBMS.
  • Good knowledge on AutoSys scheduler is desired.
  • Good knowledge on Agile / Scaled Agile principles.
  • Excellent communication skills (both spoken and written).
  • Document all technical and system specifications documents for all ETL processes and perform unit tests on all processes and prepare required programs and scripts.
  • Assist in the ongoing development of technical best practices for data movement, data quality, data cleansing and other ETL-related activities.
  • Design, implement, and continuously expand data pipelines by performing extraction, transformation, and loading activities.
  • Gather requirements and business process knowledge in order to transform the data in a way that’s geared towards the needs of end users.
  • Maintain and improve already existing processes.
  • Ensure that the data architecture is scalable and maintainable.
  • Work with the business in designing and delivering correct, high quality data.
  • Investigate data to identify potential issues within ETL pipelines, notify end-users and propose adequate solutions.

Education

Any Graduate