Cloud Data Architect - Data Modeler

Accountabilities

• Lead the design, implementation, governance, and continuous improvement of cloud-based data architecture, platforms, models, and pipelines across ingestion, storage, transformation, integration, migration, archival, and operations.
• Design scalable and secure cloud data platforms, including data lakes, lakehouses, and data warehouses, supporting operational workloads, reporting, analytics, and AI/ML use cases.
• Architect multi-tenant cloud and hybrid environments supporting relational, NoSQL, distributed SQL, multimodal, event-driven, and streaming data technologies.
• Establish logical and physical data isolation, tenant-level security, resource allocation controls, and architecture patterns aligned with federal security, privacy, and governance requirements.
• Develop and maintain logical, physical, dimensional, relational, analytical, and operational data models, ensuring consistency, scalability, performance, and alignment with business and technical requirements.
• Define data flows, structures, standards, naming conventions, metadata, lineage, documentation, and governance practices across the data lifecycle.
• Establish integration patterns for ETL/ELT pipelines, APIs, change data capture, and downstream consumption supporting business intelligence, data products, and AI/ML solutions.
• Implement and optimize operational databases, document storage, indexing services, schemas, and secure data APIs using infrastructure-as-code approaches.
• Monitor and optimize database and query performance through automated tuning, indexing, capacity management, and other performance-engineering practices.
• Develop and operationalize data classification standards, including metadata requirements, security controls, workflows, training materials, and adoption support.
• Partner with governance, security, application development, business intelligence, and data engineering teams to ensure architecture decisions comply with applicable policies and standards.
• Develop data migration strategies covering profiling, mapping, testing, anomaly management, validation, and rollback procedures.
• Develop archival strategies covering archive creation, migration, storage tiers, retention schedules, and access controls.
• Design, test, and implement high-availability and disaster-recovery strategies and support batch and real-time data exchange with enterprise systems.
• Maintain architecture diagrams, data models, performance metrics, metadata, lineage, audit-ready documentation, and records of design decisions under version control.
• Evaluate data architecture technologies, tools, and platforms and provide recommendations supported by documented analysis and rationale.
• Support the development of technology roadmaps spanning data engineering, analytics, reporting, and AI/ML capabilities.
• Work within an Agile federal environment, collaborating with technical and business stakeholders while mentoring junior data modelers or engineers as needed.

Requirements

• Master’s degree in information systems or a related field with 12+ years of general experience and 10+ years of specialized experience, or an equivalent combination of education and experience. Alternative experience equivalencies include 18+ years with a high school diploma, 16+ years with an associate degree, 14+ years with a bachelor’s degree, or 11+ years with a doctorate.
• Extensive experience designing enterprise data architecture using AWS data services and modern cloud application patterns, with AWS experience strongly preferred.
• Deep expertise developing scalable, secure operational data models and architecture patterns supporting application functionality, service integration, and high-availability workloads.
• Strong experience with relational, NoSQL, and graph database modeling for transaction-intensive and enterprise-scale environments.
• Extensive experience architecting cloud data platforms that support analytics, reporting, business intelligence, and AI/ML at scale.
• Hands-on experience with data lakes, lakehouses, data warehouses, and change-data-capture-enabled ingestion patterns.
• Experience with platforms such as Snowflake, Databricks, or Amazon Redshift, including data modeling and associated tooling.
• Experience with analytics and BI platforms such as Tableau, Power BI, or Amazon QuickSight.
• Strong knowledge of master data management (MDM), data governance, metadata management, data lineage, and governance integration.
• Experience modernizing legacy data environments and leading or supporting enterprise cloud migration strategies.
• Practical understanding of infrastructure-as-code, ETL/ELT, APIs, data integration, security controls, resilience, cost optimization, and platform performance.
• Experience working in regulated, compliance-driven, or government environments where security, privacy, classification, and auditability are critical.
• Familiarity with cloud-based data platforms and their core services, particularly AWS.
• Ability to establish data governance guardrails covering integrity, security, resilience, cost efficiency, and operational quality.
• Experience mentoring junior data engineers or data modelers and contributing to technical standards and best practices.
• Strong analytical and problem-solving skills, with the ability to evaluate complex issues and formulate clear technical recommendations.
• Excellent written, verbal, and presentation skills, including the ability to communicate effectively with senior customer stakeholders.
• Strong consultant mindset with demonstrated ability to build trusted relationships, work independently, collaborate across teams, and translate complex technical concepts into practical solutions.
• Ability to identify and apply relevant industry tools, methodologies, emerging technologies, and best practices.
• Preferred certifications include Certified Data Management Professional (CDMP), Snowflake SnowPro Advanced, Databricks Certified Data Professional, AWS Certified Data Analytics – Specialty, AWS Certified Solutions Architect – Professional, or AWS Certified Data Engineer.
• U.S. citizenship is not required, and no security clearance or Public Trust designation is required for this position.

Benefits

• Expected salary range of $169,604–$229,464, with actual compensation determined by experience, geographic location, and applicable contractual requirements.
• Full-time, 100% remote position with no required travel.
• 40-hour standard workweek.
• Multiple medical plan options, including plans with Health Savings Accounts (HSAs).
• Dental and vision insurance options.
• 401(k) retirement plan with company matching and pre- and post-tax contribution options.
• Flexible workweeks where applicable to support work-life balance.
• Paid vacation, sick, and personal leave.
• Approximately 15 days of paid leave per calendar year for new employees, subject to applicable conditions and proration.
• 10 paid holidays annually.
• Paid parental, military, bereavement, and jury duty leave.
• Paid Family Leave of up to 160 hours within a rolling 12-month period for eligible employees.
• Short- and long-term disability coverage.
• Life insurance and accidental death and dismemberment coverage.
• Personal accident, critical illness, and business travel and accident insurance options.
• Opportunities to work on high-impact cloud, data, analytics, AI/ML, and modernization initiatives supporting the U.S. federal government.
• Access to a broad technology environment and opportunities for professional growth and technical leadership.