Data Architect / Engineer - Assistant Vice President

Overview

Provide technical and architectural leadership for enterprise cybersecurity data, analytics, and AI capabilities, defining and delivering scalable data architectures, Lakehouse platforms, data models, integration frameworks, and AI-ready data foundations.

What you'll do

• 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 you'll need

• 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.
• 15+ years of experience across Data Architecture, Data Engineering, enterprise data platforms, cloud, analytics, AI, or related technology disciplines.
• Bachelor's degree in Computer Science, Engineering, Information Systems, Cybersecurity, or a related discipline, or equivalent experience.
• Proven experience architecting and delivering enterprise-scale data platforms and Lakehouse solutions.
• Strong experience with Python, SQL, PySpark, Databricks, ETL/ELT, distributed processing, data modeling, and AWS or comparable cloud platforms.
• Experience with CI/CD, automated testing, monitoring, data governance, and engineering best practices.
• Strong written, verbal, analytical, and stakeholder communication skills.

Nice to have

• Experience in cybersecurity, financial services, regulated industries, or large enterprise environments.

Details

• Individual contributor role with strong cross-functional collaboration expectations.
• Requires sound judgment when working with sensitive cybersecurity, risk, operational, and regulated data.
• Balance exploratory data science with production-minded analytical delivery and stakeholder communication.
• Location: Bangalore, India.