Principal Engineer – Data Engineering, AI & Distributed Systems
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 employer, metro location, and high-demand GenAI/data skillset create very high candidate competition.
Requires deep enterprise data, cloud, and finance domain expertise, limiting cross-industry transferability.
Explicit 7+ years plus mandatory large-scale data, cloud, GenAI, and regulatory experience enforce strict filtering.
Job Description
Structured overview of role & requirementsAbout This Role
Provide technical leadership and strategic direction for enterprise data platforms, AI, distributed systems, and cloud-native architectures impacting global-scale business capabilities.
Drive architecture, modernization, and governance for large-scale data engineering, software engineering, AI/GenAI solutions, and cloud platforms with measurable goals around scalability, security, and operational excellence.
Advise and influence senior leadership on technology strategy, emerging tech evaluation, enterprise AI governance, and cross-functional alignment across multiple business and technical stakeholders.
Minimum Requirements
7+ years of engineering experience (including software engineering, data engineering, or equivalent combined experience).
Hands-on experience with data engineering tools and platforms (e.g., Spark, Kafka, Snowflake, Databricks) and development frameworks (Java, Spring Boot).
Experience leading cloud-native architectures on Azure or GCP and familiarity with container orchestration (Docker, Kubernetes).
Proven leadership in high-complexity, enterprise-scale engineering environments with responsibility for design, governance, and modernization initiatives.
Ideal Candidate Profile
Recognized technical leader with deep expertise in data engineering, Java/Spring Boot microservices, and generative AI, capable of influencing CIO/CTO-level stakeholders and mentoring senior engineers.
Experienced in designing and delivering large-scale, secure, resilient cloud-native solutions integrating real-time analytics, AI (including LLMs, RAG pipelines), and governed enterprise data platforms.
Strategic thinker with demonstrated ability to align engineering roadmaps with business objectives in large matrixed organizations, balancing innovation with operational risk and compliance requirements.