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