Data Engineer-Data Modeling

Introduction

Embarking on a career with IBM Consulting means engaging in long-lasting client partnerships and collaborating on a global scale. You will have the opportunity to work alongside prominent companies across various sectors, assisting them in navigating their hybrid cloud and AI transformations. Backed by our strategic alliances, cutting-edge IBM technology, and Red Hat, you will possess the resources necessary to effect meaningful change and enhance client outcomes. At IBM Consulting, a culture driven by curiosity fosters achievement. You will be empowered to question the status quo, investigate new concepts, and devise innovative solutions that yield tangible results. Our environment emphasizes growth and empathy, prioritizing your long-term career progression while appreciating your distinct skills and experiences.

Your Role And Responsibilities

In the capacity of a Data Engineer with a focus on Data Modeling, your role will involve the design and implementation of data models for applications and associated systems, converting business requirements into logical and physical data frameworks. You will leverage your knowledge of data modeling tools and methodologies to provide high-quality solutions.

Your Primary Responsibilities Will Include

• Design Data Models: Develop and execute data models for applications and related systems, ensuring they align with business requirements.
• Apply Data Modeling Expertise: Employ your skills in data modeling tools and techniques, such as ERWin, MDM, and/or ETL, to create logical and physical data models.
• Translate Business Needs: Convert business requirements into logical and physical data models, ensuring they fulfill business objectives and are accurately implemented.
• Implement Data Models: Execute data models for applications and related systems, maintaining data integrity and consistency across platforms.
  
  

Preferred Education

Master's Degree

Required Technical And Professional Expertise

• Data Modeling Tools: Proficient in data modeling tools like ERWin, MDM, and/or ETL, with the capability to apply this expertise to create logical and physical data models.
• Data Model Design: Proven experience in designing and implementing data models for applications and related systems, ensuring they meet business needs.
• Logical and Physical Data Models: Demonstrated ability to develop logical and physical data models that translate business requirements into technical solutions.
• Data Integrity and Consistency: Experience in implementing data models that guarantee integrity and consistency of data across systems.
• Business Requirements Analysis: Skilled in analyzing business needs and requirements to guide data model design and implementation.
  
  

Preferred Technical And Professional Experience

• Data Warehousing Knowledge: Familiarity with data warehousing principles and practices, including data governance and data quality, is advantageous for this position.
• Advanced Data Modeling: Knowledge of advanced data modeling strategies, such as data vault and dimensional modeling, can enhance your capability to design and implement sophisticated data models.
• Big Data Technologies: Understanding of big data technologies, including Hadoop and NoSQL databases, can be beneficial for creating scalable data models.