Distinguished Data and Analytics Engineer Distinguished Data and Analytics Engineer 23 hours ago Be among the first 25 applicants Lensa is the leading career site for job seekers at every stage of their career. Our client, Cisco, is seeking professionals in San Jose, CA. Apply via Lensa today! Application window is expected to close on: May 30, 2025 Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received. Meet the Team Join our dynamic Cybersecurity CTO team—a forward-looking group at the heart of driving security innovation, strategy, and architecture across the organization. We operate as trusted advisors and hands-on technologists, guiding the enterprise through complex security challenges while shaping the future of cybersecurity capabilities. With deep expertise in emerging threats, secure architecture, product security, and cutting-edge technologies, we lead initiatives that elevate security posture, streamline security engineering, and enable business outcomes. This team plays a critical role in aligning security with enterprise priorities, influencing executive decision-making, and delivering scalable, high-impact solutions that secure our global operations and products. Your Impact You are a proven technical leader with a passion for building robust data foundations in the cybersecurity domain. You thrive at the intersection of data engineering, analytics, and strategic business enablement, and you have a track record of modernizing legacy data environments. You excel at introducing cutting-edge data technologies that transform how organizations leverage data for trust, security, and AI-driven initiatives. You combine deep technical expertise with strong leadership and communication skills, enabling you to navigate complex, enterprise-scale challenges and influence cross-functional stakeholders. Define the Data Strategy: Develop and communicate a clear vision for enterprise-wide data architecture and analytics capabilities that support cybersecurity initiatives. Modernize Legacy Data Projects: Lead the transformation of existing data pipelines, data stores, and analytics frameworks, ensuring enhanced performance, scalability, and reliability. Introduce Modern Data Technologies: Assess, select, and implement contemporary data platforms and tooling (e.g., cloud-based data warehouses, streaming technologies, ML platforms) in areas that are early in their data maturity. Establish Trust in Security Data: Design and implement processes, governance, and controls to maintain data integrity and verifiable trust across all security-related data sources. Accelerate AI Initiatives: Partner with data science and AI teams to ensure high-quality, ready-to-use data sets that feed advanced analytics, machine learning, and AI models in support of threat detection and broader security objectives. Drive Cross-Functional Collaboration: Work closely with security engineers, product teams, and leadership to align on key strategic objectives, manage roadmaps, and ensure seamless integration of data-driven solutions. Mentor & Develop Talent: Build and lead a high-performing data team. Coach and mentor junior engineers, instill data best practices, and create a culture of continuous learning and innovation. Minimum Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or related field (or equivalent experience). 10+ years of experience in data engineering, data architecture, or analytics, with at least 5 years in a leadership capacity. Proven track record of leading end-to-end data modernization efforts and large-scale data platform deployments. Expertise with cloud-based data platforms (AWS, Azure, or GCP) and associated data engineering and analytics toolchains. Familiarity with cybersecurity use cases (SIEM, SOAR, threat detection, vulnerability management, etc.) and how data powers these functions. Strong knowledge of data governance, data security, compliance, and best practices around privacy. Preferred Qualifications Experience partnering with data science teams to build machine learning pipelines and operationalize AI models. Knowledge of DevOps practices as applied to data (DataOps), including CI/CD pipelines for data and analytics workloads. Hands-on experience with data visualization tools (e.g., Tableau, Power BI) and advanced analytics platforms. Familiarity with emerging data technologies (e.g., real-time streaming, graph databases, unstructured data processing). Excellent program/project management skills, with a track record of delivering complex data initiatives on time and within budget.
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