Data Architect

Responsibilities

The Enterprise Data Architect drives the implementation of the Data and Analytics strategy by designing enterprise data architectures, strategies and solution recommendations in support of business strategies. The data architect leads complex and advanced architectural design, evaluation, planning, testing, and operational support across the organization's.

• Assesses and determines governance, stewardship, and frameworks for managing data across the organization.
• Champions enterprise data management best practices.
• Provides consultation during strategic planning, prioritization, and implementation projects.
• Leads design of high-level conceptual and logical models that facilitate a cross system/cross functional view of data requirements.
• Performs Security, Sharing, and Safeguarding Management Analysis
• Develops and delivers long-term goals for data modeling and standards. Identifies and develops opportunities and strategies for data reuse, migration, or retirement.
• Leads and conducts data capacity planning, life cycle, duration, usage requirements, feasibility studies and related tasks.
• Establishes methods and procedures for tracking data quality, completeness, redundancy, and improvement.
• Establishes processes for governing the identification, collection, and use of corporate metadata and takes steps to assure metadata accuracy, validity and quality. Provides leadership to system and local work groups.
• Uses a high degree of independent judgment and competence to achieve results and resolve significant issues.
• Provides input to management on tactical issues.
• Designs Zero Trust Architecture Data Pillar implementation and solutions to complex data sets.
• Coordinates with business stakeholders to translate requirements into technical specifications to drive enterprise data architecture, data security, and artificial intelligence security.
• Standardizes data flow processes, reducing operational inefficiencies.
• Assesses data integration issues and develops tools that improve data quality.
• Develops policies that aligned data architecture with strategic goals.
• Implements security measures in collaboration with Information Security, ensuring data privacy and compliance with federal regulations.

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Qualifications

• The candidate will have 8+ years of experience in data governance, strategic planning, and data management.
• Experience with complex LLM data tools and data science methodology
• Data Modeling experience
• Zero Trust Architecture
• Data Security, Architecture and AI Security
• In absence of years of experience, certifications or past work may be used to show the level of experience needed to perform at this level.
• Excellent communications and collaboration skills with both technical and non-technical audiences required.
• Strong documentation, analytical thinking, requirements analysis, and stakeholder engagement skills required.

Planet Technologies is the leading provider of Microsoft Consulting Services to public sector and commercial organizations. Planet has significant experience in deploying business intelligence, cloud services, unified communications, and systems management with an emphasis building, deploying, and managing custom solutions that transform the business operations of federal government agencies.

Planet Technologies does not discriminate in employment opportunities, terms and conditions of employment, or practices. All qualified applicants will receive consideration for employment without regard to race, age, gender, religious or political beliefs, national origin or heritage, disability, sexual orientation, protected veteran status, or any characteristic protected by law. Federal Agency Clearance Requirements may require up to a 10-year background investigation - US Citizenship (clearable) is required.

Salaries for Data Architects at Planet Technologies range from $110,000 and $200,000. Several factors will impact final pay offered to a successful candidate including but not limited to the type and years of experience within the job, clearance level, the type of years and experience within the industry, education, training, etc.

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.