Address
Form of workJob 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.
