This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description Courses will be taught in Spanish. Candidates must be fluent in both English and Spanish and pass a fluency test. APUS faculty demonstrate a strong commitment to learning, teaching, interaction with students and faculty, service to our communities of practice, and scholarship. Bilingual faculty (English/Spanish) effectively communicate in both languages, both verbally and in writing, to support our diverse student population. United by the common goal of inspiring academic excellence in students with a broad range of interests and experiences consistent with the Community of Inquiry Framework, as adopted by American Public University System (APUS) for cognitive presence, teaching presence, and social presence: - Faculty play a vital role in creating a rewarding online learning experience for students by engaging them, challenging them, and supporting them. - Contribute to and participate in a range of activities related to effectiveness and excellence in teaching and student retention. - Maintain expertise in their discipline, adhere to APUS guidelines, processes, and methods. - Remain responsive to mentoring and coaching that fosters ongoing professional growth. When Applying: - Upload a CV and a copy of unofficial transcripts, master's degree and above. Student issued/unofficial copies are acceptable. Please do not send us official copies, unless specifically asked. General Work Requirements: - All APUS faculty are required to complete the “Engaging the First‐Year Student Certification” course (APUS110), offered through the Center for Teaching and Learning (CTL). It must be completed within six months of the hire date. - Graduate Faculty must complete the Graduate Faculty Certification (APUS501) within 90 days of hire. - Specific requirements related to your Graduate / Undergraduate Faculty designation, duties, and performance expectations are outlined on the Course Assignments issued with respect to each course to be taught. - You agree to comply with and be bound by all policies with respect to work product and intellectual property rights set forth in the APUS Faculty Handbook, the APUS Employee Handbook, the APEI Employee Handbook, and applicable Course Assignments. - You will be expected to perform your duties in a remote, professional working environment of your choice. APUS assumes no responsibility for injuries occurring in your selected workspace or damages related to your real or personal property resulting from your employment with APUS. Qualifications - Doctoral degree in Business, Analytics, Engineering, Computer Science, Operations Management, Management, or a closely related field from a regionally accredited institution is required. - Five or more years of experience in a data science field is required. - Bilingual fluency in English and Spanish is required. - Candidates must be able to communicate effectively in both languages, verbally and in writing. - Demonstrated proficiency in English and Spanish with the ability to convey complex information clearly and accurately across diverse audiences. - Proficiency testing in both English and Spanish will be part of the application process to confirm language fluency levels required for the position. - Ability to translate and interpret information, ensuring accuracy and cultural sensitivity in communication. - Experience supporting or engaging with Spanish-speaking students preferred. - Online college-level teaching experience is required. - Record of excellence in teaching. Benefits - Information regarding our faculty benefits may be found here: Faculty Benefits . Company Description American Public University System (APUS) is an Online University based in Charles Town, WV. Our University has over 100,000 students. Our emphasis is educating our nation’s military and public services communities with quality and affordable education. APUS provides partnership and commitment in helping students realize the dream of a higher education and the opportunities that brings. It is the policy of American Public University System (APUS) to afford equal opportunity to all qualified persons. We treat all qualified individuals equally as to their recruitment, hiring, assignments, advancements, compensation, and all other terms and conditions of employment. American Public University System (APUS) does not discriminate on the basis of race, color, religion, creed, sex, age, national origin, sexual orientation, or physical, mental, or sensory disability, or any other characteristic protected by law. #LI-Remote

• Own problems end-to-end from ambiguous business questions to stable technical solutions • Act as a technical architect and strategic thought partner • Partner with senior stakeholders to define success metrics • Design technical approach and build production-ready data systems • Translate business needs into well-modeled data foundations • Lead A/B test design, statistical evaluation, and causal analysis • Translate complex analytical findings into clear, actionable recommendations • Establish modeling, documentation, and data quality standards

• Design, implement, and manage scalable data pipelines and analytics platforms. • Build and maintain dbt models to support customer projects and internal decision making. • Work with internal stakeholders to ensure data products are research-ready and aligned with customer needs • Implement and manage data instrumentation and product analytics tooling (e.g. Mixpanel) to ensure accurate tracking and reporting • Identify opportunities for optimizing data workflows and proactively address technical debt. • Partner with Engineering, Data Science, and Commercial teams to translate business and client needs into reliable, scalable data solutions

• Help define and evolve enterprise data engineering blueprints, including data mesh, medallion architecture, and hybrid cloud data platforms. • Set strategic direction for data platforms, tools, and services (e.g., Snowflake, GCP BigQuery, dbt, Kafka, Airflow/Prefect) in alignment with future-state architecture and business priorities. • Architect and design highly scalable, resilient, cost optimal and secure data platforms. • Lead the design and implementation of next-generation data platforms, ensuring fault tolerance, high availability, and optimal performance for petabyte-scale data. • Establish and enforce organization-wide best practices for data pipeline development, CI/CD for data workflows, automated deployment playbooks, and robust rollback strategies. • Lead technology evaluation and adoption, proactively researching, evaluating, and championing the integration of cutting-edge data technologies, frameworks, and methodologies. • Define and scale enterprise knowledge management frameworks that ensure consistent documentation, discoverability, and reusability of data assets across domains. • Establish and govern standards for metadata management, data lineage, architectural diagrams, and runbooks. • Lead the design of federated governance models that empower domain-aligned teams to operate autonomously while conforming to centralized policies, frameworks and playbooks. • Collaborate with data governance, compliance, and security teams to operationalize policy-as-code frameworks for data retention, access control, and PII handling. • Advocate for and enable self-service knowledge discovery through tightly integrated cataloging tools (e.g., Alation, Collibra) and automated documentation generators. • Ensure robust documentation and versioning standards are embedded in CI/CD workflows for pipeline code, transformation logic, and schema changes. • Architect implementation of scalable, automated data quality frameworks that evaluate data at rest and in motion spanning completeness, timeliness, consistency, accuracy, and integrity. • Lead integration of data quality rules, metrics, and health indicators directly into orchestration layers (e.g., Prefect, Airflow) and transformation frameworks (e.g., dbt). • Evangelize a culture of data trust and transparency by integrating data quality insights into user-facing dashboards, alerts, and product health reports. • Identify and promote enterprise-wide data opportunities through thought leadership, white papers, reference architectures, and innovation labs. • Act as technical advisor to senior executives on data modernization, AI readiness, and platform consolidation strategies. • Serve as a strategic translator between complex business challenges and modern data architecture by leading domain-level and cross-domain data product strategy engagements. • Lead the design of enterprise-grade data products that align with OKRs, business transformation goals, and operational needs ensuring value realization across functional areas like supply chain, marketing, store ops, or customer satisfaction. • Architect and operationalize a unified enterprise-wide semantic layer, metrics store, and business logic abstraction that powers dashboards, self-service analytics, and machine-readable APIs. • Lead initiatives to unify KPIs, standardize metric definitions, and streamline business logic through reusable models. • Design composable data assets and feature stores that enable real-time and offline access patterns for ML models, AI agents, and decision orchestration systems. • Lead readiness initiatives for integrating data systems with LLM-powered agents and copilots, ensuring robust grounding data, latency optimization, and lineage tracking. • Drive innovation in analytics automation, including anomaly detection, agent-triggered insights. • Serve as champion for complex analytics transformations, ensuring technical feasibility, business value realization, and adoption. • Drive culture change around data stewardship and accountability by embedding governance responsibilities into platform tooling and engineering workflows. • Lead internal communities of practice, workshops, and code reviews to disseminate modern data practices. • Mentor senior engineers across data and analytics engineering, elevating technical acumen and architectural judgment. • Influence hiring and team design decisions, supporting the scaling of high-performing, and collaborative data teams. • Represent the organization in external forums (conferences, meetups, technical alliances) and establish credibility as an industry thought leader.