Job
Description
Introduction Joining the IBM Technology Expert Labs teams means you'll have a career delivering world-class services for our clients. As the ultimate expert in IBM products, you'll bring together all the necessary technology and services to help customers solve their most challenging problems. Working in IBM Technology Expert Labs means accelerating the time to value confidently and ensuring speed and insight while our clients focus on what they do best—running and growing their business. Excellent onboarding and industry-leading learning culture will set you up for a positive impact, while advancing your career. Our culture is collaborative and experiential. As part of a team, you will be surrounded by bright minds and keen co-creators—always willing to help and be helped—as you apply passion to work that will positively impact the world around us. Your Role And Responsibilities This Candidate is responsible for: DB2 installation and configuration on the below environments. On Prem Multi Cloud Redhat Open shift Cluster HADR Non-DPF and DPF. Migration of other databases to Db2(eg TERADATA / SNOWFLAKE / SAP/ Cloudera to db2 migration) Create high-level designs, detail level designs, maintaining product roadmaps which includes both modernization and leveraging cloud solutions Design scalable, performant, and cost-effective data architectures within the Lakehouse to support diverse workloads, including reporting, analytics, data science, and AI/ML. Perform health check of the databases, make recommendations and deliver tuning. At the Database and system level. Deploy DB2 databases as containers within Red Hat OpenShift clusters Configure containerized database instances, persistent storage, and network settings to optimize performance and reliability. Lead the architectural design and implementation of solutions on IBM watsonx.data, ensuring alignment with overall enterprise data strategy and business objectives. Define and optimize the watsonx.data ecosystem, including integration with other IBM watsonx components (watsonx.ai, watsonx.governance) and existing data infrastructure (DB2, Netezza, cloud data sources) Establish best practices for data modeling, schema evolution, and data organization within the watsonx.data lakehouse Act as a subject matter expert on Lakehouse architecture, providing technical leadership and guidance to data engineering, analytics, and development teams. Mentor junior architects and engineers, fostering their growth and knowledge in modern data platforms. Participate in the development of architecture governance processes and promote best practices across the organization. Communicate complex technical concepts to both technical and non-technical stakeholders. Required Technical And Professional Expertise 15+ years of experience in data architecture, data engineering, or a similar role, with significant hands-on experience in cloud data platforms Strong proficiency in DB2, SQL and Python. Strong understanding of: Database design and modelling(dimensional, normalized, NoSQL schemas) Normalization and indexing Data warehousing and ETL processes Cloud platforms (AWS, Azure, GCP) Big data technologies (e.g., Hadoop, Spark) Database Migration project experience from one database to another database (target database Db2). Experience in deployment of DB2 databases as containers within Red Hat OpenShift clusters and configure containerized database instances, persistent storage, and network settings to optimize performance and reliability. Excellent communication, collaboration, problem-solving, and leadership skills. Preferred Technical And Professional Experience Experience with machine learning environments and LLMs Certification in IBM watsonx.data or related IBM data and AI technologies Hands-on experience with Lakehouse platform (e.g., Databricks, Snowflake) Having exposure to implement or understanding of DB replication process Experience with integrating watsonx.data with GenAI or LLM initiatives (e.g., RAG architectures). Experience with NoSQL databases (e.g., MongoDB, Cassandra). Experience in data modeling tools (e.g., ER/Studio, ERwin). Knowledge of data governance and compliance standards (e.g., GDPR, HIPAA). soft skills. Show more Show less
