Data Analyst

Introduction
At IBM work is more than a job – it’s a calling: To build. To design. To code. To consult. To think along with clients and sell. To make markets. To invent. To collaborate. Not just to do something better but to attempt things you’ve never thought possible. Are you ready to lead in this new era of technology and solve some of the world’s most challenging problems? If so lets talk.

Your Role and Responsibilities
The proposed job role requires that the individual is knowledgeable in the areas of Digital Marketing as well as Pharma and Life Sciences industry. One critical requirement for this role is to have an understanding on Genentech’s data on how to effectively extract transform and process their data. Should also have been part of the Genentech project particularly as a member of the Interactive Marketing team. This will help enable to collaborate more effectively in gathering the requirements to build a more detailed technical design that will help the client produce quality deliverables.

Required Technical and Professional Expertise
Deep experience in designing and developing ETL (Extract-Transform-Load) jobs using any of the following Digital Insights Hive SQL AWS Glue Python and Pyspark
– Certification or familiarity with GCP and AWS cloud
– Should also have an experience in using SQL Server and Google Big Query as the backend database
– Should also be familiar on critical Data warehousing fundamental Familiarity with tools like JIRA Confluence and Google Docs will also be needed to help perform his daily operational activities.
– Understanding of the movement of data coming from the source and then transforming those data base on defined business rules and then loading those to the target data mart tables that will eventually become the data source of the Tableau reporting tool that will be use by the client.

Preferred Technical and Professional Expertise
• – Liaison between Business Vendor/Agency and the IT Team
• – Manages the Data Standards and Governance
• – Assists in developing the data requirements
• – Leads and develops all data model activities
• – Manages the logical and physical model changes
• – Develops the data base indexes and partitioning design
• – Manages DDL (Data Definition Language)
• – Manages and Develops high medium and low complexity ETL programs
• – Performs Unit Testing ETL mappings and workflows
• – Verifies that Unit Tests are documented and have passed
• – Assists in the transition of the ETL solution from development/test to production
• – Resolves defects
• – Provide support for defects resolution