Data Engineer-Data Modeling

A career in IBM Consulting is built on long-term client relationships and close collaboration worldwide. You’ll work with leading companies across industries, helping them shape their hybrid cloud and AI journeys. With support from our strategic partners, robust IBM technology, and Red Hat, you’ll have the tools to drive meaningful change and accelerate client impact. At IBM Consulting, curiosity fuels success. You’ll be encouraged to challenge the norm, explore new ideas, and create innovative solutions that deliver real results. Our culture of growth and empathy focuses on your long-term career development while valuing your unique skills and experiences. As a Data Engineer specializing in Data Modeling, you will design and implement data models for applications and related systems, translating business needs into logical and physical data models. You will apply your expertise in data modeling tools and techniques to deliver high-quality solutions. Your primary responsibilities will include: • Design Data Models: Design and implement data models for applications and related systems, ensuring alignment with business needs and requirements. • Translate Business Needs: Translate business needs into logical and physical data models, utilizing expertise in data modeling tools and techniques. • Apply Data Modeling Expertise: Apply knowledge of data modeling tools and techniques, including ERWin, MDM, and/or ETL, to deliver robust data models. • Implement Data Solutions: Implement data models and related systems, ensuring seamless integration with existing infrastructure. • Optimize Data Models: Continuously review and optimize data models to ensure they meet evolving business needs and requirements. • Data Modeling Expertise: Experience with data modeling tools and techniques, including ERWin, MDM, and/or ETL, with the ability to apply this expertise to deliver high-quality data models. • Logical and Physical Data Models: Experience in designing and implementing logical and physical data models that meet business needs and requirements. • Business Needs Translation: Experience with translating business needs into technical data models, ensuring alignment with business requirements. • Data Solution Implementation: Experience in implementing data models and related systems, ensuring seamless integration with existing infrastructure. • Data Model Optimization: Experience in continuously reviewing and optimizing data models to ensure they meet evolving business needs and requirements. • Advanced Data Modeling Tools: Experience with data modeling tools beyond ERWin, MDM, and ETL, such as PowerDesigner or IBM InfoSphere Data Architect, to further enhance data model design and implementation. • Data Governance Knowledge: Familiarity with data governance principles and practices to ensure data models align with organizational data management policies and standards. • Cloud-Based Data Modeling: Exposure to cloud-based data modeling tools and technologies, such as Snowflake or Amazon Redshift, to support scalable and flexible data model implementation. India Data & Analytics Hybrid Professional Bangalore, IN (0063) IBM India Private Limited