Principal Data Curation Architect

Johns Hopkins Applied Physics Laboratory•Laurel, MD

20d

About The Position

The Principal Data Curation Architect will develop, launch, and continuously improve data management and curation capabilities within a sophisticated research and classified IT environment at the Johns Hopkins University Applied Physics Laboratory. The role addresses decades of scientific, engineering, and mission data that need improved organization, documentation, governance, discovery, and lifecycle management to support research, mission teams, and AI/ML-enabled applications. Working closely with data owners, IT, cybersecurity, security officers, technical teams, and leadership, the position establishes practical standards and processes that make data more discoverable, understandable, governed, and reusable. The role combines IT project management, data governance, process improvement, technology implementation, stakeholder engagement, and data-curation practices.

Requirements

Bachelor's degree in library/information science, data science, scientific research, or a related field.
At least 2 years of professional experience leading technology projects, application/data-management initiatives, or related technical projects.
Demonstrated proficiency curating large, structured datasets, including data quality assessment, normalization, and traceable documentation of curation actions.
Demonstrated experience establishing or improving technology processes, workflows, governance practices, or operational capabilities.
Experience leading multidisciplinary teams involving technical experts, business/mission partners, quality assurance, security, and/or compliance teams.
Background leading the lifecycle of technology systems, applications, or data-intensive solutions.
Solid understanding of FAIR data principles and research data-management practices.
Proficiency in gathering requirements, analyzing business/mission needs, developing implementation approaches, managing risks, and delivering technology solutions.
Experience developing standard operating procedures, governance documentation, process standards, and implementation plans.
Ability to communicate effectively with technical teams, researchers, senior leadership, security staff, and program leadership.
Demonstrated ability to work in a complex environment with competing priorities and ambiguous requirements.
Ability to obtain a Secret security clearance; eligibility requires U.S. citizenship and meeting requirements for access to classified information.

Nice To Haves

Master's, Ph.D., or other advanced degree in a relevant scientific, engineering, or information field.
Experience supporting federal research, scientific, engineering, healthcare, or military organizations, such as UARCs, FFRDCs, national laboratories, NIH, or DoD.
Advanced knowledge of databases, SQL, ETL pipelines, and reporting automation tools.
Familiarity with metadata standards such as Dublin Core, DataCite, DDI, and schema.org/Dataset, and catalog platforms such as Dataverse, CKAN, DSpace, and Fedora.
Experience preparing data and documentation for AI/ML reuse, and familiarity with AI/ML data-readiness concepts such as Data Cards, Datasheets for Datasets, Croissant, or FAIR4ML.
Active PMP, Scrum, or other recognized project-management certification, alongside experience with Agile/Scrum, SDLC, or continuous improvement.

Responsibilities

Lead projects to establish and implement data-management and curation capabilities, including objectives, scope, schedules, budget estimates, and measures of success.
Develop, implement, and manage end-to-end data pipelines and lifecycle workflows, including intake, assessment, cleaning, documentation, quality review, versioning, retention, and archiving.
Lead the inventory and assessment of legacy and active research data, working with data owners to manage and enrich raw information so it remains accurate, searchable, and useful over time.
Create and implement data governance processes, roles, responsibilities, standards, and operating procedures.
Train, teach, and mentor data owners and consumers on collating, formatting, documenting, and curating data for downstream use and AI/ML readiness.
Drive evaluation, selection, configuration, and implementation of data catalogs, metadata-management tools, reporting automation, and analytics solutions in collaboration with IT and cybersecurity.
Establish lightweight metadata and documentation standards aligned with FAIR principles and applicable sponsor, security, and data-management expectations.
Coordinate technical teams and subject-matter experts to prepare and package datasets for downstream research, analytics, and AI/ML use.
Develop project plans, schedules, status reports, risk registers, and executive-level briefings to advise leadership on priorities, risks, and resource requirements.
Identify opportunities to improve processes, systems, and tools through automation, integration, and technology modernization.
Develop and maintain standard operating procedures, templates, guidance, and training materials.

Benefits

Robust education assistance program.
Retirement contributions and retirement plans.
Paid time off.
Medical insurance.
Dental insurance.
Vision insurance.
Life insurance.
Short-term disability insurance.
Long-term disability insurance.
Flexible spending accounts.
Training and development.
Potential sign-on bonus, relocation benefits, locality allowance, or discretionary payments for exceptional performance, subject to eligibility and applicable policy or contractual designation.