Sr. Director of Enterprise Architecture and Data Science
Listed on 2026-02-16
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IT/Tech
Data Engineer, Cloud Computing, Data Security, Data Science Manager
Sr. Director of Enterprise Architecture and Data Science
POSITION SUMMARY: The Sr. Director of Enterprise Architecture and Data Science will own the full enterprise architecture (data, applications, infrastructure, integrations, and security) alongside the enterprise data architecture, ELT pipelines, risk data integration, and data science/AI outcomes. This hands-on leadership position combines deep expertise in modern data platforms and enterprise-wide system design with the vision to deliver predictive analytics, machine learning models, and AI-driven innovations that generate measurable revenue growth, optimize operations, and enhance experiences across our high-volume call center, field sales teams, and core systems (Salesforce, Net Suite, Leap, Five9).
ESSENTIAL JOB FUNCTIONS:
- Define, own, and evolve the comprehensive enterprise architecture roadmap spanning data, applications, infrastructure, integrations, networking, security, and cloud platforms.
- Provide architectural governance and strategic oversight across the entire technology stack, ensuring alignment, scalability, interoperability, and cost efficiency.
- Create and Lead cross-functional architecture reviews, technology standardization, vendor evaluations, and long-term roadmap planning in partnership with Application, Infrastructure, Product, and Security leaders.
Data Architecture Leadership
- Own the design, implementation, governance, and evolution of the enterprise data architecture, including Snowflake Lakehouse, Airbyte ELT pipelines, dbt transformations, Verisk risk data integration, Five9/Leap data flows, and Snowflake Cortex AI capabilities.
- Ensure seamless, high-quality data integration across core applications (Salesforce, Net Suite, Leap, Five9) and external sources to enable near real-time and batch analytics.
- Lead cloud data modernization, infrastructure-as-code practices, and performance optimization for resilient data flows supporting offices, remote agents, and field operations.
Data Science & AI Strategy Execution
- Develop and deliver predictive models, machine learning solutions, and AI initiatives (e.g., lead scoring, inventory forecasting, customer propensity, call center optimization, risk modeling).
- Identify and prioritize high-impact use cases in collaboration with Sales, Marketing, Operations, and Call Center leaders to drive revenue lift, improve conversion rates, and enhance operational efficiency.
- Achieve attributable business outcomes through AI, including live lead-scoring and forecasting models.
Reliability, Security & Governance
- Maintain ultra-high availability (98–99.9% pipeline and system uptime) for data platforms and integrated revenue-critical systems.
- Champion enterprise-wide security architecture, data governance, quality assurance, best practices (Zero Trust, encryption, access controls), and compliance (e.g., PCI-DSS).
- Oversee monitoring, incident response, disaster recovery, and geographic redundancy for data and critical systems.
Team & Organizational Leadership
- Provide strategic direction and mentorship to data engineering, architecture, and cross-functional technology teams, foster innovation and collaboration.
- Informative in technology strategy, budget planning, vendor governance, and key performance indicators.
- Serve as final escalation point for critical data delivery, architectural decisions, integration issues, and high-severity incidents.
- Partner with Application, Infrastructure, Product, and business leaders to align initiatives with company goals; present progress and data to executive leadership.
Position
Qualifications:
- Bachelor’s or Master’s Degree in Computer Science, Data Science, Engineering, Statistics, or related field (advanced degree preferred) or equivalent work experience.
- 12+ years in enterprise architecture, integration architecture, and data architecture; 7+ years building and leading data science/ML teams with demonstrated business impact.
- Hands-on expertise with modern data stack:
Snowflake (including Cortex AI), Airbyte, dbt, ELT pipelines, Data Lakehouse architecture, and external data integration (e.g., Verisk, Five9 contact center data). - Proven enterprise architecture experience,…
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