Data Systems Architect

Association of Universities for Research in Astronomy•Boulder, CO

11d•$130,000 - $176,000•Hybrid

About The Position

The National Solar Observatory seeks a Data Systems Architect to lead the technical design of the Data Management System (DMS) for the Next-Generation Ground-Based Solar Observing Network (ngGONG), a six-station global telescope network currently in its design phase. The DMS will support the scientific data lifecycle—from ingestion and processing through archival and user access—and serve research and operational space-weather applications in near-real-time. Building on an existing reference design, the architect will own DMS architecture, requirements, interfaces, and technical designs. The design phase emphasizes architecture, technical coordination, and review preparation, supported by targeted prototypes and benchmarks. Technology choices remain open and will be evaluated against scientific, performance, cost, and operational needs. This is an individual-contributor position with technical leadership and mentoring responsibilities. The architect owns DMS technical decisions within project standards and change control, coordinating shared interfaces and services with High-Level Software (HLS), Data Center, and IT teams. The position reports to the Software and Controls Manager, who retains responsibility for priorities, staffing, budget, and project-wide alignment. Scientists own scientific algorithms and acceptance criteria; the architect owns integrating them into reliable, traceable processing workflows. The position supports the currently funded design phase through September 2028. Continuation into later phases depends on project approval and funding. The role is based on the University of Colorado campus in Boulder, with at least three days per week in the office and up to two days working from home. Travel is expected to be limited during the design phase, though visits to GONG stations or other observatories may occur. The desired start date is as soon as practical. The annual salary range is $130,000 to $176,000, depending on skills, qualifications, experience, and internal equity. AURA offers 24 vacation days per year plus holidays, automatic retirement plan contributions, and other benefits. Work primarily involves computer-based design and analysis, documentation, and collaboration; occasional observatory visits may involve high-elevation locations.

Requirements

Bachelor’s degree in computer science, software engineering, engineering, physics, astronomy, or a related field, or equivalent practical experience.
At least ten years of professional software engineering or software architecture experience, including technical leadership in the architecture and delivery of complex data-processing or distributed software systems.
Experience translating requirements into architecture and interfaces, evaluating technologies, documenting tradeoffs, and leading technical reviews.
Experience across the data lifecycle, with depth in ingestion, processing, storage, or archives, including APIs, data models, metadata or provenance, and reliable workflows.
Experience with performance analysis, capacity planning, and reliability in data-processing or distributed systems.
Strong software development skills in a language such as Python, Java, C++, or Go on Linux, with version control, automated testing, configuration management, and observability.
Ability to estimate effort, assess risks, communicate tradeoffs to multidisciplinary teams, and mentor engineers.

Nice To Haves

Experience designing or operating automated data-processing systems with explicit latency or service-level requirements, including capacity planning, workload prioritization, performance validation, and failure recovery.
Scientific or astronomical data experience, especially multi-instrument or multi-station pipelines, calibration, data-quality assessment, and reproducible reprocessing.
Experience with high-throughput or petabyte-scale systems, distributed processing, archives, and workflow orchestration across on-premises, high-performance computing, or cloud environments.
Experience preparing requirements, ICDs, estimates, and evidence for formal design reviews.
Familiarity with scientific data formats, scientific Python libraries, and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles.

Responsibilities

Create and maintain a coherent DMS architecture, subsystem designs, measurable requirements, subsystem specifications, and verification plans; keep the Conceptual Design, Product Breakdown Structure (PBS), Design Requirements Document (DRD), and subsystem specification aligned.
Define Interface Control Documents (ICDs), APIs, data contracts, metadata and provenance models, data handoff interfaces, and data-custody responsibilities with data-acquisition teams.
Design scientific processing and calibration workflows based on stakeholder requirements, including reference datasets, quality metrics, and acceptance tests; support consistent multi-station products, reproducible reprocessing, and continuity with relevant preexisting datasets.
Consult with current observatory operations and data-processing teams to incorporate operational experience into the design.
Design ingestion, processing, archival, discovery, and distribution services, including programmatic access and automated delivery to operational consumers; address data integrity, retention, and long-term preservation.
Develop end-to-end latency budgets, capacity models, and workload priorities for live processing, delayed arrivals, and reprocessing; use representative prototypes and benchmarks to validate deadlines, performance margins, and recovery under constrained resources or connectivity.
Evaluate compute, storage, networking, workflow, and deployment needs to determine hosting strategies across cloud, hybrid, and on-premises environments in collaboration with infrastructure owners.
Produce design descriptions and decision records supported by trade studies, prototypes, and benchmarks, and contribute to the Software Development Plan.
Design development, test, and operational environments that support pipeline evolution and reprocessing without disrupting operational delivery.
Define availability, monitoring, and recovery approaches, including visibility into data completeness, backlog, and product latency; incorporate allocated NSO cybersecurity controls and agree on shared operational responsibilities with IT and infrastructure providers.
Prepare estimates, schedules, risks, procurement inputs, and design-review evidence; resolve review findings, maintain controlled design artifacts, lead technical reviews, and mentor contributing engineers.
Deliver a coherent conceptual design for Conceptual Design Review in Summer 2027 and mature the design, interfaces, technology selections, and verification plans for Preliminary Design Review in Summer 2028.
Demonstrate latency feasibility and performance margins, with estimates and an implementation plan appropriate to each review.
Develop the DMS technical scope, execution plan, and cost estimates for the proposal covering final design and construction.