IBM Data Engineering Job Openings 2025 | Data Platforms – Google – WFH (Hybrid)

Qualifications

Required technical and professional expertise

• Develop/Convert the database (Hadoop to GCP) of the specific objects (tables, views, procedures, functions, triggers, etc.) from one database to another database platform Implementation of a specific Data Replication mechanism (CDC, file data transfer, bulk data transfer, etc.).
• Expose data as API Participation in modernization roadmap journey Analyze discovery and analysis outcomes Lead discovery and analysis workshops/playbacks Identification of the applications dependencies, source, and target database incompatibilities.
• Analyze the non-functional requirements (security, HA, RTO/RPO, storage, compute, network, performance bench, etc.).
• Prepare the effort estimates, WBS, staffing plan, RACI, RAID etc. .
• Leads the team to adopt right tools for various migration and modernization method

Preferred technical and professional experience

• You thrive on teamwork and have excellent verbal and written communication skills.
• Ability to communicate with internal and external clients to understand and define business needs, providing analytical solutions
• Ability to communicate results to technical and non-technical audiences

Your Role and Responsibilities:

As an Associate Software Developer at IBM you will harness the power of data to unveil captivating stories and intricate patterns. You’ll contribute to data gathering, storage, and both batch and real-time processing.

Collaborating closely with diverse teams, you’ll play an important role in deciding the most suitable data management systems and identifying the crucial data required for insightful analysis. As a Data Engineer, you’ll tackle obstacles related to database integration and untangle complex, unstructured data sets

In this role, your responsibilities may include:

• Implementing and validating predictive models as well as creating and maintain statistical models with a focus on big data, incorporating a variety of statistical and machine learning techniques
• Designing and implementing various enterprise search applications such as Elasticsearch and Splunk for client requirements
• Work in an Agile, collaborative environment, partnering with other scientists, engineers, consultants and database administrators of all backgrounds and disciplines to bring analytical rigor and statistical methods to the challenges of predicting behaviour’s.
• Build teams or writing programs to cleanse and integrate data in an efficient and reusable manner, developing predictive or prescriptive models, and evaluating modelling results