Job Title : Data Architect – AI Platform
Location : Hybrid
Department : Engineering / Data Platform
About the Role
We’re looking for a self-motivated, hands-on Data Architect with a deep background in AI and machine learning to design and evolve our next-generation data platform.
This role is central to building the data and AI backbone that serves both our Business Intelligence (BI) teams and our Core Product engineering groups. You’ll architect and implement the systems that transform raw data into AI-driven insights — powering smarter analytics, automation, and product experiences.
You won’t just define the vision — you’ll build proofs of concept (POCs) , validate with cross-functional teams, and evolve successful prototypes into scalable, production-grade solutions.
Key Responsibilities
- Architect the Modern Data & AI Platform :
- Design a unified data architecture that supports analytics, machine learning, and AI-driven insights for both internal and customer-facing use cases.
- Build the AI Insight Stack :
- Develop the foundational components — from data ingestion and transformation to feature engineering, embeddings, and inference — that enable AI to surface patterns and insights within data.
- Be Hands-On and Experimental :
- Create POCs to validate architectural decisions, data models, and AI workflows, ensuring they deliver measurable business value.
- Bridge Data and AI Workflows :
- Design systems that make data easily consumable for both BI tools and AI pipelines — ensuring consistency and real-time readiness.
- Collaborate Across Teams :
- Partner with BI, data science, and product engineering to align data platform capabilities with analytical, AI, and product needs.
- Ensure Data Quality and Governance :
- Define standards for lineage, observability, and quality to ensure reliable, trusted data for both human and AI consumers.
- Leverage Modern Cloud and AI Stack :
- Utilize tools such as Snowflake, dbt, Airflow, Kafka, Spark, and cloud AI services (AWS SageMaker, Vertex AI, etc.) to enable scalable and efficient data operations.
- Guide Strategic Direction :
- Advise leadership on emerging data and AI technologies, influencing how the company extracts intelligence from data at scale.
Qualifications
Required :
8+ years of experience in data architecture, data engineering, or AI platform design .Proven experience building the end-to-end stack for AI-driven data insights — from raw data ingestion to model inference and insight delivery.Strong background in cloud-native data ecosystems (AWS, GCP, or Azure).Proficiency in Python, SQL , and modern data tools (Snowflake, Spark, dbt, Kafka, Airflow, etc.).Deep understanding of AI / ML workflows — feature stores, vector databases, model training, and deployment pipelines.Track record of building and validating POCs that successfully informed scalable architecture decisions.Excellent communication skills and ability to collaborate across data, AI, and engineering teams.Preferred :
Experience integrating Generative AI and LLM-based systems (RAG, embeddings, vector stores).Background in data API design and real-time data infrastructure for AI applications.Familiarity with MLOps / LLMOps frameworks (MLflow, Kubeflow, SageMaker, Vertex AI).Understanding of data governance, ethics, and responsible AI practices.What Success Looks Like
A unified, AI-ready data platform powering both BI insights and AI product features.Accelerated delivery of AI-driven insights across the company.Strong data foundation enabling rapid experimentation and reliable AI deployment.Working POCs that demonstrate the value of combining data architecture with AI intelligence.Why Join Us
This is a unique opportunity to build the intelligence layer of the company — creating the data foundation that powers every AI-driven decision, product feature, and insight. You’ll architect, prototype, and deliver the systems that transform data into action, working at the frontier of data engineering and applied AI .
Interested candidates, please send their resumes to iqbal.kaur@birdeye.com
Regards
Iqbal Kaur