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
1. Spearhead the architecture of QualityStages in IBM DataStage Next Generation for CP4D, overseeing the development and maintenance of critical components, including Investigate, Standardize, Match, and Survival functionalities.
2. Architect the Advanced Stages in IBM DataStage Next Generation, leading the design for the seamless porting of new Advanced Stages from IBM DataStage On-Premises to IBM DataStage Next Generation. Drive the migration of potential stages and features to DataStage Next Generation on Public Cloud / CP4D.
3. Collaborate closely with product owners and the UX design team, coordinating with other product teams like Project, Dataview, and Connection teams to devise solutions aligned with customer requirements and performance criteria. This encompasses aspects such as Canvas design, OSH generation, Asset storage, and Runtime, ensuring a comprehensive end-to-end user experience.
4. Enhance and maintain the XML Schema Library service within IBM DataStage Next Gen, leveraging expertise in XSD, JSON schema, and WSDL to enhance XML Schema Library continuously.
5. Enhance existing automatic data parsing component for various file types, including CSV, sequential, and complex flat files.
6. Improve and maintain the Asset Browsing and Preview frontend for various connectors in DataStage Next Generation, covering RDBMS, data warehouses, data lakes, big data, and stream data storage systems.
7. Lead code reviews within the Advanced Stages and Quality Stage squad to ensure adherence to best practices in code quality and appropriate design across the development process, encompassing languages like C/C++, Java, JavaScript, and more.
8. Address critical customer issues using various tools to identify and resolve issues, enhancing existing methods for reproducing, tracing, analyzing, and debugging.
9. Utilize tools such as Jenkins/Travis CI and Artifactory to establish automation pipelines for building, deploying, and testing environments.
10. Collaborate closely with global pre-sales and post-sales teams to ensure the successful delivery and deployment of IBM DataStage products.
11. Stay abreast of the latest industry trends, driving innovation and technological improvements in the DataStage Next Generation product.

Required Technical and Professional Expertise
1. Hold a Master’s degree in Computer Science, Information Technology, or a related field.
2. Familiar with React, Webpack, Node.js, Dust, Carbon Component, and Elyra-Canvas for frontend development.
3. Hands on experiences in debugging issues by applying containerization and deploying DataStage applications using Docker, OpenShift/Kubernetes, with tracing facilitated by LogDNA/NGINX, and remote debugging capabilities using Gdb, JVM, and Node.js.
4. Demonstrate a minimum of 15 years of experience in C and C++, with a deep understanding of object-oriented programming (OOP) and design patterns for abstracting business models.
5. Showcase 10 years of experience in Java, with a strong foundation in ETL and machine learning (ML).
6. Exhibit 6 years of experience in Node.js and JavaScript, with expertise in React, Webpack, and Node.js.

Preferred Technical and Professional Expertise
1. In-depth understanding of DataStage On-Premises and Next Generation product, with proven experience in designing and integrating large data projects with DataStage ETL processes.
2. Hands-on experience with IBM Cloud Pack for Data’s Hybrid Cloud Infrastructure, including IBM Authorization, Asset, Connection APIs, familiarity with Asset Browser, and Dataview components.
3. Expertise in a broad range of SQL and NoSQL database connectors in DataStage, covering DB2, Oracle, MySQL, MS SQL, PostgreSQL, Informix, MariaDB, MongoDB, Redis, Azure SQL Database, Azure Cosmos DB, Azure DataLake Storage, HDFS, Hive, Impala, HBase, Cassandra, Snowflake, Teradata, AWS S3, and GCS.
4. Deep understanding of various storage systems, such as IBM MQ, Kafka, SAP, Box, Elasticsearch, Dropbox, and more.
5. Proficiency in utilizing cloud services such as Amazon Web Services, IBM Cloud, Microsoft Azure, and Google Cloud Platform.