Lead DataStage Developer

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 of 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 Datawarehouse 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 databases 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)

Documents 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 thats 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