This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Cloud Data Architect - Data Modeler based in United States.
This senior role will lead the architecture and modernization of cloud-based data infrastructure supporting a major federal technology transformation program.
You will design scalable data platforms, models, pipelines, and integration patterns across the full data lifecycle.
The position combines hands-on data architecture with governance, security, migration, analytics, and AI/ML enablement.
You will work closely with data engineers, application teams, security specialists, governance leaders, and senior government stakeholders.
Your work will help establish secure, high-performing, and resilient data capabilities that support operational decision-making and enterprise analytics.
The environment is highly regulated and Agile, requiring strong technical judgment, documentation discipline, and a customer-focused consulting mindset.
This is an opportunity to shape foundational cloud data architecture for a large-scale modernization initiative with nationwide impact.
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.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.
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