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Last Updated Date May 25, 2021 |

The Data Engineering Architect is responsible for the full Development lifecycle from requirements gathering through design, architecture and implementation. The Data Engineering Architect is responsible for setting up the road map for the Data Engineering platform and identifies necessary technologies to be associated with or within the solution architecture. The Data Engineering Architect works closely with developers and business users to identify, develop and implement techniques to improve productivity, increase efficiency, mitigate risks and resolve issues. 

Reports to: 

  • Enterprise Architect 
  • Project Manager 
  • Director of Solution Architecture 


  • Clearly understand business challenges, their impact and the type of solution needed to effectively address these challenges. 
  • Act as a visionary, a strategist, and a thought leader for a solution area. Surveys the market for insights, directions and vendors and conducts Proof of Concepts to evaluate options for possible future solutions. 
  • Designs “best in class” enterprise solutions to overcome a specific business problem utilizing tools and technologies available in the enterprise (e.g., Solution Design for SAP Integration). 
  • Participates in Enterprise Architecture Board Reviews (EARB) to present, evaluate and certify solutions to support multiple internal projects (e.g., certifying a Data Virtualization solution to support Enterprise Virtualization projects). 
  • Identifies existing patterns and guides teams on selecting the right solution (e.g., if a Data Masking solution is already standardized within the organization, educates internal teams about the existing solution). 
  • Helps Project Managers with implementation plan estimates and provides knowledge sharing and guidance to development teams. 


  • Ability to understand business requirements and convert them into solution designs. 
  • Understands industry standard data integration architectures. 
  • Understands enterprise integration tools and technical solution components. 
  • Has strong Business Analysis and problem-solving skills. 
  • Familiarity with the Data Engineering architecture framework. 
  • Strong presentation and communication skills. 
  • Good judgment and a pragmatic approach to delivering solutions that optimize architecture activities across company needs, business constraints and technological realities. 

Recommended Training 

  • Corresponding data storage vendor’s product training 
  • Agile development 
  • Business Intelligence and Analytics 


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