Data Architect

Job Description

ABOUT XENONSTACK

XenonStack is the fastest-growing   Data and AI Foundry for Agentic Systems , enabling enterprises to gain   real-time and intelligent business insights .

We deliver innovation through :

Agentic Systems for AI Agents   →   akira.ai

Vision AI Platform   →   xenonstack.ai

Inference AI Infrastructure for Agentic Systems   →   nexastack.ai

Our mission is to accelerate the world’s transition to   AI + Human Intelligence   by designing   scalable, reliable, and AI-ready data platforms   that power next-gen enterprise systems.

THE OPPORTUNITY

We are seeking a   Data Architect   to design, govern, and optimize   enterprise data ecosystems   that fuel   LLM training, RAG pipelines, Vision AI, and multi-agent systems .

This is a strategic role that blends   data engineering, governance, and architecture leadership   — ensuring that XenonStack and its customers operate on   trusted, scalable, and intelligent data infrastructure .

KEY RESPONSIBILITIES

Data Architecture & Strategy

Define and implement   data platform blueprints   across cloud and hybrid environments.

Design architectures for   data lakes, warehouses, and real-time streaming pipelines .

Ensure alignment with   business goals, AI readiness, and compliance requirements .

Enterprise Data Modeling & Governance

Establish standards for   data modeling, lineage, quality, and master data management .

Implement   governance frameworks   to meet enterprise and regulatory needs (GDPR, SOC2, HIPAA).

AI & Analytics Enablement

Architect   data pipelines   that feed into   LLMs, RAG systems, and Vision AI workflows .

Collaborate with AI / ML teams to design   high-quality, labeled, and observable datasets .

Technology & Integration

Define reference architectures for   ETL / ELT, vector databases, and knowledge graph integration .

Evaluate and select technologies across   AWS, Azure, GCP, and open-source data ecosystems .

Leadership & Collaboration

Mentor   data engineers and platform engineers   on best practices.

Partner with   Product, AgentOps, and Security teams   to ensure reliable, compliant, and cost-optimized data systems.

SKILLS & QUALIFICATIONS

Must-Have

8–12 years in   data engineering, architecture, or analytics platform leadership .

Proven expertise in   data modeling, ETL / ELT pipelines, and distributed data systems .

Hands-on with   big data and analytics frameworks   (Spark, Kafka, Delta Lake, Databricks).

Strong knowledge of   cloud-native data ecosystems (AWS Redshift / Glue, Azure Synapse / Data Factory, GCP BigQuery / Dataflow) .

Proficiency in   SQL, Python, and data orchestration frameworks (Airflow, dbt) .

Deep understanding of   data governance, compliance, and security best practices .

Good-to-Have

Experience with   vector databases (Pinecone, Weaviate, FAISS) and knowledge graphs .

Familiarity with   LLM / AI data pipelines and agentic system data needs .

Certifications in AWS / Azure / GCP data engineering or architecture.

Industry exposure to   BFSI, GRC, SOC, or regulated enterprise environments .

WHY SHOULD YOU JOIN US?

Agentic AI Product Company

Architect data systems that power   enterprise-grade AI agents .

A Fast-Growing Category Leader

Join one of the fastest-growing   AI Foundries , trusted by Fortune 500 enterprises.

Career Mobility & Growth

Progress into roles such as   Principal Data Architect, Head of Data Platforms, or AI Systems Architect .

Global Exposure

Work with enterprises worldwide on   mission-critical data systems .

Create Real Impact

Your designs will directly influence   AI adoption, enterprise intelligence, and business outcomes .

Culture of Excellence

Our values —   Agency, Taste, Ownership, Mastery, Impatience, and Customer Obsession   — give you autonomy to innovate and accountability to deliver.

Responsible AI First

Ensure data platforms are   not just powerful, but trustworthy, explainable, and compliant .

XENONSTACK CULTURE – JOIN US & MAKE AN IMPACT!

At XenonStack, we believe in   shaping the future of intelligent systems . We foster a   culture of cultivation   built on bold, human-centric leadership principles, where   deep work, simplicity, and adoption   define everything we do.

Our Cultural Values

Agency   – Be self-directed and proactive.

Taste   – Sweat the details and build with precision.

Ownership   – Take responsibility for outcomes.

Mastery   – Commit to continuous learning and growth.

Impatience   – Move fast and embrace progress.

Customer Obsession   – Always put the customer first.

Our Product Philosophy

Obsessed with Adoption   – Making AI-ready data architectures accessible and enterprise-grade.

Obsessed with Simplicity   – Turning complex data challenges into seamless, intuitive systems.

Be a part of our mission to   accelerate the world’s transition to AI + Human Intelligence   — by   architecting the trusted data platforms that power enterprise AI adoption .

Requirements

Must-Have 8–12 years in data engineering, architecture, or analytics platform leadership. Proven expertise in data modeling, ETL / ELT pipelines, and distributed data systems. Hands-on with big data and analytics frameworks (Spark, Kafka, Delta Lake, Databricks). Strong knowledge of cloud-native data ecosystems (AWS Redshift / Glue, Azure Synapse / Data Factory, GCP BigQuery / Dataflow). Proficiency in SQL, Python, and data orchestration frameworks (Airflow, dbt). Deep understanding of data governance, compliance, and security best practices.