Senior Architect (Data, Cloud, AI)

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.

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.

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.

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.

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.

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

Education Assistance Program

Professional development opportunities

LinkedIn Learning

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