Lead Architect; Enterprise Data​/AWS

For decades, DTN has been the silent force behind some of the world’s most critical industries—helping businesses navigate complexity, uncertainty, and risk with smarter, faster decisions. From agriculture to energy to weather intelligence, our proprietary Operational Decisioning Platform transforms raw data into decision-grade insights—enabling companies to optimize supply chains, ensure market stability, and safeguard infrastructure against disruption. We don’t follow trends—we set the standard for precision, trust, and operational impact.

DTN is at an exciting inflection point. Building off a foundation of financial strength, profitability, and industry trust, we’re accelerating growth and expanding our global footprint. Our purpose-built solutions—powered by AI and honed by decades of vertical expertise—are helping some of the world’s most significant enterprises thrive amid operational constraints and uncover new opportunities in a fast-changing world.

DTN is seeking a Lead Architect (aka, Architect at Large) to join our Engineering team and help shape the future of DTN’s technology strategy and data-driven innovation. This role partners closely with the Chief Architect, engineering leadership, and product teams to design scalable, next-generation solutions that leverage DTN’s extensive data assets. The Architect at Large provides architectural governance, drives best practices, and leads technical decision-making to ensure secure, reliable, and forward-looking systems across the organization.

• Collaborate with engineering managers and technical teams to design and oversee implementation of scalable, high-performance architectural solutions.
• Partner with the Chief Architect to ensure alignment with DTN’s overall technology strategy and architectural standards.
• Create and maintain architectural documentation, including design reviews and technical standards.
• Identify, prioritize, and mitigate technical debt and operational risks related to data engineering, warehousing, ETL, and related systems.
• Facilitate design reviews and guide technical trade-off discussions across engineering teams.
• Establish and promote architectural best practices across technical guilds and business sectors.
• Provide influence and leadership across teams without direct reporting authority.

• 8+ years of experience in data modeling and data engineering, including large-scale data warehousing and processing environments.
• Strong expertise in designing and building applications, ETL systems, and data management solutions within the AWS ecosystem.
• Experience with API design, cloud-native data pipelines, and distributed systems; familiarity with Graph
  
  QL and semantic architectures is a plus.
• Proven ability to design, document, and present system-level architectures and technical trade-offs.
• Experience integrating CI/CD tools and infrastructure-as-code solutions (e.g., Terraform, Git Lab, Bitbucket Pipelines, Bamboo).
• Strong understanding of data cataloging, master data management, and data transformation across diverse formats and sources.
• Experience working within Agile and Scrum development environments.
• Ability to influence and lead across teams in a matrixed organization.

• Competitive Salary
• Unlimited PTO
• Flexible working hours
• Remote work model (position dependent)
• Competitive Medical, Dental and Vision Insurance Plans
• 6% 401K matching
• Unlimited access to 13k+ courses via learning platform to support employee career advancement
• Employee Assistance Program (EAP)

The targeted hiring base pay range for this position is between $131,000 and $175,000
. DTN is a pay-for-performance organization, which means there is the opportunity to advance your compensation with performance over time. The actual base pay offered for this position will be dependent upon many factors, including but not limited to: prior work experience, training/education, transferable skills, business needs, internal equity and applicable laws. The targeted hiring base pay range is subject to change and may be modified in the future.

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