Sensory AI Hiring! Full Time Senior Data Architect - Data Platform Lead in Selangor - Ricebowl

Senior Data Architect / Data Platform Lead

 Sensory AI - Ella Autonomous Retail Intelligence Platform

Employment Type: Fractional / Full-Time

Role Summary

Sensory AI is building the data and AI infrastructure layer for Ella, our autonomous robot cafe platform and the first commercial endpoint for our real-world Physical AI operating system.

We are hiring a hands-on Senior Data Architect / Data Platform Lead to design and build the data foundation that allows Ella endpoints to observe, report, recover, optimise, learn and improve through SensoryOS.

This is not a traditional reporting or dashboard role. This person will define the schemas, pipelines and data products that support Guardian Agent, Avatar Agent, Ella Store Agent, CrownD runtime, robotic telemetry, customer sessions, store operations, fleet learning and OTA improvement loops.

Why This Matter

Every Ella deployment generates rare real-world data across robotics, payments, customer interaction, inventory, staff workflows, machine reliability and autonomous operations. When structured correctly, this data becomes Sensory AI's long-term moat.

The core principle for this role is simple: every important event must connect state -> decision -> action -> outcome.

Key Responsibilities

• Design the canonical data architecture for Ella endpoints and SensoryOS fleet intelligence.
• Define schemas for stores, devices, robot/machine state, customer sessions, orders, payments, inventory, promotions, incidents, agent actions, staff interventions, OTA updates and model/prompt/policy versions.
• Build event ingestion pipelines from CrownD, robot/IoT systems, POS, Avatar, Guardian Agent and SensoryOS services.
• Implement schema validation, data contracts, quality checks, versioning and auditability for production data.
• Create the data foundation for Guardian Agent self-healing, incident classification, root cause learning and predictive maintenance.
• Create the data foundation for Avatar Agent conversation logs, customer feedback, service recovery and staff guidance workflows.
• Create the data foundation for Ella Store Agent recommendations across promotions, pricing, inventory, menu performance, customer experience and margin optimisation.
• Build analytical tables, feature tables and dashboard-ready datasets for store performance and fleet benchmarking.
• Work with engineering, robotics, product, UI/UX and operations teams to translate real-world store workflows into structured data.
• Support closed-loop OTA learning by tracking update versions, rollouts, outcomes, regressions and rollback events.

Core Data Domains

Domain

What Must Be Captured

Store / Device Identity

Store ID, device ID, location type, operator/franchisee, software version, hardware BOM, model/policy version.

Machine / Robot State

Robot state, coffee machine state, IoT readings, fault codes, recovery attempts, local edge state.

Customer Session / Order

Session ID, order flow, payment, queue/wait time, preparation, collection, refund/cancel status.

Inventory / Ingredient Usage

Stock level, batch, supplier, consumption, refill, waste, expiry, stockout and reorder signal.

Incident / Guardian

Fault, severity, root cause, detection source, agent diagnosis, recovery action and outcome.

Avatar / CX

Conversation event, customer intent, staff prompt, delay message, sentiment, feedback and resolution.

Promotion / Pricing

Promo trigger, discount, margin floor, redemption, uplift, cannibalisation and profit impact.

Agent Action

Agent, intent, input state, tool call, approval status, execution result and measured outcome.

OTA / Learning Loop

Update package, rollout cohort, version, performance, regression, rollback and adoption.

Required Experience

• 5+ years in data engineering, data architecture, analytics engineering or production data systems.
• Strong SQL and data modelling skills.
• Hands-on experience building data pipelines, data warehouses, data marts or lakehouse-style architectures.
• Experience with event-driven data, APIs, telemetry, observability, IoT, product analytics or operational systems.
• Strong understanding of data quality, validation, schema evolution and production reliability.
• Ability to work hands-on with engineering teams, not only produce architecture documents.
• Ability to work with ambiguity and convert messy operational workflows into clean data models.
• Clear written communication and strong documentation habits.

Strongly Preferred Experience

• IoT, robotics, industrial automation, hardware telemetry, edge devices or fleet operations.
• Retail, F&B, e-commerce, payments, logistics, customer journey analytics or promotion analytics.
• Time-series data, event streaming, MQTT, Kafka, Pub/Sub, NATS or similar systems.
• ML feature stores, ML data pipelines, LLM/agent logging or agent evaluation datasets.
• A/B testing, experimentation, promotion ROI, pricing, inventory forecasting or reliability analytics.
• Experience with BigQuery, Snowflake, Redshift, ClickHouse, Databricks, Postgres, dbt, Airflow, Dagster, Prefect or equivalent tools.