"Alerted.org

Job Description

The Senior Enterprise Data Architect is a critical role responsible for establishing and

driving the enterprise-wide data architecture vision, strategy, and framework to support business objectives. This position focuses on creating a robust data foundation by collaborating with business data stakeholders, data product teams, and cross-functional IT teams to ensure data architecture aligns with business value and strategic goals. The role defines data governance standards, data models, and integration patterns to enable scalable, secure, and efficient data solutions across the enterprise. The Senior Enterprise Data Architect will anticipate industry trends, assess emerging

technologies, and provide thought leadership to optimize the organization's data ecosystem,

ensuring data-driven decision-making and operational excellence. This role will guide data product teams and solution architects by establishing standards and best practices, fostering data reusability, and ensuring consistency in data design and delivery. The Senior Enterprise Data Architect will also lead proof-of-concept initiatives to evaluate innovative data technologies and their impact on the enterprise data landscape, effectively communicating findings to influence the data strategy and roadmap.

ESSENTIAL FUNCTIONS

• Define and maintain the enterprise data architecture strategy, including data

models, integration frameworks, governance standards, and data lifecycle management, to support business goals.

• Collaborate with business data stakeholders and data product teams to identify

data requirements, translate business needs into technical data solutions, and align data architecture with business value.

• Develop and maintain high-level data reference models, including conceptual, logical, and physical data models, to ensure consistency and scalability across the enterprise.

• Establish and enforce data governance processes, including data quality, security,

compliance, and metadata management, to support regulatory requirements and business objectives.

• Lead architectural reviews to ensure adherence to data architecture standards, best practices, and enterprise policies.

• Identify opportunities to optimize the current data landscape by reducing redundancies, improving data integration, and enhancing data accessibility.

• Facilitate the reuse of data assets, schemas, and patterns to accelerate data product development and improve efficiency.

• Assess emerging data technologies (e.g., cloud-native data platforms, AI-driven analytics, real-time data processing) and lead proof-of-concept initiatives to evaluate their potential impact on the enterprise data strategy.

• Maintain and manage enterprise data architecture tools and repositories (e.g., data

catalogs, metadata management platforms) to support data discovery and governance.

• Serve as a bridge between data product teams, solution architects, and business stakeholders to ensure alignment with the enterprise data architecture strategy.

• Drive the Data Architecture Community of Practice to promote thought leadership, share industry trends, and foster collaboration across teams.

• Consult on the use of data standards and emerging technologies to support business initiatives, ensuring compliance with enterprise data policies.

• Develop and document data architecture standards and guidelines for data product

teams and solution architects to reference when designing solutions.

• Communicate strategic data themes and business drivers to technical and nontechnical stakeholders, ensuring clarity and alignment.

• Manage the data portfolio, identifying needs for data platform upgrades, training, or

new technology implementations.

• Support the organization's Emergency Operation Plan (EOP) by ensuring data availability and integrity during critical operations.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to [email protected] learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

• Minimum of 12 years of experience in IT, with at least 7 years in data architecture or enterprise data management role.

• TOGAF certification is a must, reflecting expertise in enterprise architecture frameworks and methodologies.

• Extensive expertise in data architecture, best practices, data modeling, governance, and integration standards.

• Proven ability to collaborate across multiple functions (e.g., business units, data engineering, security, infrastructure) to deliver data solutions.

• Experience with enterprise data management tools (e.g., Collibra, Informatica, Alation, or similar).

• Strong knowledge of cloud data platforms (e.g., AWS, Azure, Google Cloud) and their strengths and weaknesses in data architecture design.

• Familiarity with data governance frameworks and compliance requirements (e.g., GDPR, CCPA, or industry-specific regulations).

• Hands-on experience with data modeling tools and methodologies (e.g., ERwin, PowerDesigner, or similar).

• Working knowledge of change management, release management, and data lifecycle management processes.

• Strong analytical skills with the ability to identify, analyze, and resolve complex data-related challenges. • Certification in data architecture or related frameworks (e.g., DAMA-DMBOK).

• Experience with real-time data processing or big data technologies (e.g., Kafka, Spark).

• Knowledge of AI/ML data architectures and their application in enterprise settings.