About Ellucian:

Ellucian powers innovation for higher education, partnering with approximately 3,000 customers across 50 countries, serving more than 21 million students. Ellucian's AI-powered platform, trained on the richest dataset available in higher education, drives efficiency, personalized experiences, and strengthened engagement for all students, faculty and staff. Fueled by decades of experience with a singular focus on the unique needs of learning institutions, the Ellucian platform features best-in-class SaaS capabilities and delivers insights needed now and into the future. These solutions and services span the entire student lifecycle, including data-rich tools for student recruitment, enrollment, and retention to workforce analytics, fundraising, and alumni engagement. Ellucian's cutting-edge solutions, vast ecosystem of partners and user community of more than 45,000 provides best practices leading to greater institutional success and achieving better student outcomes.

About the Opportunity:

Ellucian is seeking a highly skilled and innovative Senior Architect to lead the architecture and technical strategy for our next-generation Data Platform and analytics solution. This role will be instrumental in transforming our current data warehouse ecosystem into a modern, scalable, cloud-native Lakehouse platform capable of supporting analytics, AI/ML workloads, agentic AI experiences, and real-time data products.

This is a hands-on architecture leadership role requiring deep expertise in data platforms, data warehouse, distributed systems, cloud technologies, and emerging AI technologies.

As a key technical leader , role offers opportunities to spearhead technical initiatives, mentor engineers at all levels, and work closely with internal product managers, experienced engineers, and cross-functional teams to design, develop, test, and deliver advanced features that enhance student success and drive higher education transformation.

Where You Will Make an Impact

Architecture & Strategy

- Build and own the target-state architecture for a next-generation Lakehouse platform.
- Develop technology roadmaps aligned with business strategy and product vision.
- Lead architectural decisions across data ingestion, storage, processing, governance, observability, security, and AI enablement.
- Establish architecture principles, standards, and reference architectures.

Platform Modernization

- Lead migration from traditional data warehouse architectures to modern Lakehouse architectures.
- Design scalable data platforms supporting structured, semi-structured, and unstructured data.
- Evaluate and drive adoption of technologies such as Apache Iceberg, Delta Lake, Apache Spark, DuckDB, Trino, Flink,



Kafka, and cloud-native analytics services.
- Design multi-tenant SaaS architectures with strong security and data isolation.

AI & Intelligent Data Platform

- Define architecture patterns enabling AI-powered data experiences.
- Design platforms supporting:
- - Generative AI applications
- Agentic AI workflows
- Retrieval-Augmented Generation (RAG)
- Vector databases and semantic search
- AI-assisted analytics and insights

- Partner with AI teams to operationalize ML and GenAI workloads.
- Evaluate emerging AI technologies and determine applicability to the platform roadmap.

Technical Leadership

- Take ownership of critical tasks from specification review through final testing and deployment, ensuring timely and high-quality delivery.
- Serve as the highest level technical authority for the platform.
- Mentor architects and senior engineers.
- Conduct architecture reviews and guide critical design decisions.
- Drive engineering excellence and technical innovation across teams.

Scalability, Reliability & Operations

- Architect for high availability, performance, resiliency, and cost optimization.
- Define observability and operational excellence standards.
- Drive platform reliability through automation and SRE practices.
- Establish governance around performance, security, compliance, and data quality.

What You Will Bring

- Experience: Bachelor / Master's degree in Computer Science, Data Engineering, AI, or related field. Overall 15+ years of software engineering exp with 7+ years of professional software development experience in a product or SaaS environment building modern Data platform.
- Deep expertise in modern data architectures including Data warehouse, Data Mesh, Data platforms.
- Deep expertise in distributed data processing frameworks, Apache Spark, Trino, Flink, Kafka.
- Experience with open table formats, Apache Iceberg, Delta Lake.

- Strong understanding of Metadata management, Lineage, observability.
- Distributed Systems: Experience designing, building, and evolving large-scale distributed systems, microservices, event-driven architectures, and highly available production services.
- Cloud and Platform Engineering: Strong knowledge of cloud platforms such as AWS, containerization, infrastructure automation, and modern operational practices for reliability,



scalability, and cost efficiency.
- Engineering Excellence: Deep experience with CI/CD, code review, test automation, observability, release engineering, and DevOps practices in modern software delivery environments.
- Security and Risk Awareness: Strong understanding of authentication, authorization, encryption, secure design, and practical application security principles in enterprise software.
- LLM and Agentic Systems Experience: Demonstrated experience building or guiding solutions that use large language models, including agent-based workflows, prompt and context design, tool orchestration, structured outputs, and human-in-the-loop validation patterns.
- Model Selection and Evaluation: Experience working with multiple LLMs or AI providers and making practical tradeoff decisions across model quality, latency, cost, reliability, safety, and enterprise suitability.
- AI Engineering Practices: Understanding of core patterns for production AI systems such as retrieval-augmented generation, evaluation frameworks, observability, prompt management, guardrails, fallback strategies, and secure handling of sensitive data.
- Judgment and Governance: Ability to evaluate AI-generated output critically, define validation standards, identify risk areas, and maintain human accountability for technical decisions and delivered outcomes.
- Technical Communication: Excellent communication, collaboration, and organizational skills, with the ability to align engineers, product partners, and stakeholders around technical direction and execution tradeoffs.
- Mentorship and Influence: Proven experience mentoring engineers, leading technical discussions, raising engineering standards, and shaping development practices across a team or organization.

What makes #Ellucianlife:

- 12 days vacation, 10 days causal leaves plus 11 public holidays

- Competitive gratuity policy
- Group insurance and Annual health checkup plan with a variety of family and wellness benefits.
- Thrive Flex Lifestyle Account (LSA) that allows you to contribute towards your health,
financial or learning interests
- 5 charitable days to support the community that supports us
- Wellness
o Headspace (mental health)
o Wellbeats (virtual fitness classes)
- RethinkCare – caregiver support
- Diversity and inclusion programs that promote employee resource groups such as: Buzzinga and Lean In Team to name a few.
- Parental leave
- Employee referral bonuses to encourage the addition of great new people to the team
- We Foster a learning culture with:
- Education Assistance Program
- Professional development opportunities
- LinkedIn Learning

#LI-SN1

#LI-Hybrid

📌 Senior Architect (Data, Cloud, AI) (Bengaluru)
🏢 Ellucian
📍 Bengaluru