Data Architect / Engineer - Assistant Vice President

Who we are looking for We are looking for an experienced Data Architect / Data Engineer, Assistant Vice President to provide technical and architectural leadership for enterprise cybersecurity data, analytics, and AI capabilities. This role will define and deliver scalable data architectures, Lakehouse platforms, data models, integration frameworks, and AI-ready data foundations. The individual will partner with cybersecurity, engineering, architecture, governance, risk, and product teams to transform complex security data into scalable, governed, and actionable solutions. What you will be responsible for As a Data Architect / Engineer, you will: ·       Architect and deliver scalable Lakehouse and enterprise data platforms, pipelines, data models, and reusable data products. ·       Define target-state data architecture, reference architectures, integration patterns, standards, and technical roadmaps. ·       Design solutions for large-scale structured, semi-structured, time-series, graph, and unstructured cybersecurity data. ·       Establish reusable frameworks for ETL/ELT, ingestion, orchestration, data quality, metadata, lineage, observability, and reconciliation. ·       Establish architecture standards for scalability, resiliency, performance, security, privacy, governance, and auditability. ·       Design AI-ready data architectures supporting LLMs, RAG, embeddings, vector/semantic search, NLP, knowledge graphs, and intelligent workflows. ·       Integrate data across cloud platforms, enterprise systems, cybersecurity platforms, and SIEM/SOAR ecosystems. ·       Provide technical leadership through architecture reviews, engineering standards, technology evaluation, and solution governance. ·       Partner with stakeholders to translate cybersecurity and business requirements into scalable data and AI solutions. ·       Mentor engineering teams and drive reusable architecture patterns, automation, and engineering best practices. What we value These skills will help you succeed in this role: ·       Strong expertise in Data Architecture, Data Engineering, Cloud Data Platforms, and AI/GenAI. ·       Deep understanding of Lakehouse architecture, distributed processing, ETL/ELT, data modeling, integration, data quality, metadata, lineage, and governance. ·       Strong hands-on skills in Python, SQL, PySpark, Databricks, Delta Lake, and cloud technologies. ·       Experience designing enterprise-scale, secure, resilient, and governed data platforms. ·       Practical knowledge of LLMs, RAG, embeddings, vector/semantic search, NLP, knowledge graphs, and responsible AI architecture. ·       Understanding of cybersecurity telemetry, SIEM/SOAR, vulnerability management, identity risk, threat intelligence, and incident data. ·       Ability to influence architecture decisions and engage effectively with technical teams, architects, product leaders, and senior stakeholders Education & Qualifications Minimum Qualifications