Senior Data Architect (Hybrid Eligible)

Requisition Id 13684 

 

­­Due to the security clearance requirements of this position, we are unable to consider EAD and Green Card holders. Additionally, Visa sponsorship of any kind is unavailable for this position (H1B, F1 (including exercising OPT), H4, J1, etc.).

 

Overview:  

We are hiring an Enterprise Data Architect to establish Enterprise IT data architecture strategies, principles, standards and policies. The successful candidate will be an authority in several technical areas including enterprise data strategy, data analysis and design, data modeling, data warehouse, data hub, data lake, data marts, business intelligence, business analytics, data integration, and extract, transfer and load (ETL) processes. This position resides in the Application Development Division of the Information Technology Services Directorate at Oak Ridge National Laboratory (ORNL).

 

You will collaborate with ITSD and others across ORNL to apply design thinking and identify creative solutions to current data challenges with future business goals and needs in mind. This role reports to the Application Development Division Director for project assignment and policy direction as part of the Enterprise Architecture team.

 

Major Duties/Responsibilities: 

Specific responsibilities of the position include, but are not limited to:

 

Enterprise Data Architecture:

• Direct and advocate for ORNL Enterprise Data Architecture.
• Maintain a deep technical knowledge of sophisticated domains (e.g. data at rest, data in transit, information security, analytics, machine learning, AI, etc.).
• Create the Enterprise level data vision and strategy, direction, goals and standards.
• Develops and maintains enterprise target data architecture to facilitate data retrieval and decision making across the enterprise.
• Maintain a comprehensive understanding and documentation of the data topology and inventory to integrate new technology requirements effectively.
• Create short and long term plans to move the laboratory to desired future state data architecture in vendor and technology neutral ways that focus primarily on business outcomes.
• Ensures redundancy of data is minimized; and when unavoidable, a reliable, “master” source is established.
• Direct the analysis of the technology environment to detect critical deficiencies and recommend solutions for improvement.
• Influence, mentor and train others in data architecture principles, standards and best practices.

 

Continuous Improvement:

• Provide continually improving set of software and systems engineering practices that minimize development friction, enhance the effectiveness of the data architecture and contribute to increasing the velocity of delivering industry-leading, quality, technology solutions.
• Perform cost/benefit analysis when researching future state capabilities.
• Ensure enterprise data solutions are scalable and adoptable according to changing business needs.
• Promote a continuous delivery pipeline and rallies the organization around a common technical vision.
• Recommend best practices (architecture, implementation, etc.).

 

Accountability:

• Uphold accountability of self and others for measurable high-quality, timely and cost-effective results.
• Expect personal and team performance to be the best and accepts responsibility for mistakes.
• Demonstrate tenacity and willingness to go the distance to get something done.

 

Communications:

• Review existing enterprise data architecture, busine