Talend Big Data Developer

Description

• Provide and develop production grade Talend Big Data jobs with considerations on meeting the IT organization’s architecture standards

• Work closely with data modelers/ system analysts on the required data interface/ requirement specifications

• Conduct technical session/ clarification with data modelers and sub-system teams prior solution design, coding and unit testing

• Document and review design of Talend Big Data jobs and interface specification

• Implement error and exception handling

• Import jobs to Talend Data Catalogue

• Integrate Talend jobs with Autosys and restart failed jobs from Autosys

• Perform technical impact assessment, source code release and deployment checklist

• Validate built conformance to required specifications

• Able to self-learn/ pick up application setup and support from vendor

• Work effectively with peers and vendors to develop, setup and support IFRS17 application and data integration

• Support SIT and UAT activities e.g., perform defect analysis, troubleshooting and fixing

• Coordinate and support Performance and Security Testing activities e.g. environment setup and test scope

• Coordinate with infrastructure team on deployment and related activities

• Provide enhancement and production support after project go live

Requirements

• Data Warehousing experience: 4 years minimum

• 3+ years working experience of Hadoop (Hortonworks) developer experience in Spark and Hive; especially Spark version 2

• Talend Big Data version 7+ Developer experience: having 3-5 years working experience deploying code to production

• 2+ years working experience in Talend Big Data version 7 on Hadoop

• Experience designing Talend job orchestration through enterprise workload automation tool like Control-M; preferably Autosys

• Working knowledge of Hortonworks data platform for data ingestions frameworks from multiple source systems e.g. AS400, Oracle Finance, MS SQL, etc.

• Have development experience using Java, PL/SQL, SQL, Python, Scala with good knowledge of data models and data flows with strong understanding of dimensional and relational databases, including: stored procedures, constraints, normalization, indexes, and security

• Insurance and financial reporting domain knowledge will be an advantage