Position: (Datastage) Data Integration Developer (Datastage)

Location: Pleasanton, CA

Duration: 12 Months +

Deliverables:

• Recommend the good practice on ETL process to extract data from disparate source transaction systems, transform and enrich the data, and load it into specific data models that are optimized for analysis and reporting.

• Facilitate the best-in-class data integration platform.

• Recommend and implement the plan for DataStage version upgrade from v. 9 10 v. 11.

• Recommend the training and mentoring plans for the transition of knowledge to current employees.

• Delivery of quality results of tasks and assignments.

Technical Knowledge and Skills:

• Extensive hands-on experience in building ETL interfaces using Datastage version 9.1 and higher version to aggregate, cleanse and migrate data across enterprise-wide MDM, Big Data, and Data Warehousing systems using staged data processing techniques, patterns and best practices.  Working knowledge and experience on DataStage 11 is a plus.

• Strong experience in full life cycle management of capturing, versioning and migrating various Datastage ETL metadata including data mapping and other data integration artifacts (such as schedulers, scripts, etc.) across environments using vendor platforms such as Data Stage,  or other equivalent tools (including open source) by establishing standards, guidelines and best practices.

• Combined experience of advanced SQL and stored procedures (in DB2, SQL Server, and/or Oracle Database Platforms) with hands-on experience of designing solutions for optimal performance and handling other non-functional aspects of availability, reliability and security of DATASTAGE ETL Platform.

• Proficiency on working with Unix and Linux servers, jobs scheduling, as well as script languages such as C, shell script (sh), AWK, and sed.

• Experience with both normalized and dimensional data models, hands-on knowledge of other data integration techniques such as database replication, change data capture (CDC) etc. and familiarity of SOA and ESB technologies and patterns.

• Technical knowledge in predictive analytics architecture and in development and deployment of predictive models is a plus.

All your information will be kept confidential according to EEO guidelines.