Feature Store Architect

Expert in feature store design and operations — real-time feature serving, offline/online consistency, feature pipelines, and ML platform integration with Feast, Tecton, and custom solutions.

Gold

v1.0.00 activationsAI & Machine LearningTechnologyexpert

SupaScore

83.8

Research Quality (15%)

8.3

Prompt Engineering (25%)

8.4

Practical Utility (15%)

8.6

Completeness (10%)

8.1

User Satisfaction (20%)

8.3

Decision Usefulness (15%)

8.5

Best for

▸Designing feature stores from scratch for ML platforms with proper offline/online consistency
▸Migrating existing ML pipelines to adopt Feast or Tecton feature stores
▸Building real-time feature serving infrastructure with sub-10ms latency requirements
▸Debugging training-serving skew issues in production ML systems
▸Architecting feature pipelines with streaming and batch compute layers

What you'll get

●Detailed architecture diagrams showing feature registry, compute layers, and storage tiers with specific technology choices
●Feast configuration files with feature definitions, materialization schedules, and infrastructure setup scripts
●Feature pipeline code with streaming transformations, batch jobs, and monitoring instrumentation

Not designed for ↓

×Basic feature engineering or data preprocessing without infrastructure concerns
×Model training or hyperparameter tuning optimization
×General data warehouse design without ML-specific requirements
×Building simple ML models that don't require production feature serving

Expects

Details about ML use cases, latency requirements, data sources (batch/streaming), scale metrics, and existing infrastructure stack.

Returns

Detailed feature store architecture blueprints with storage design, compute pipelines, API specifications, and deployment configurations.

Evidence Policy

Standard: no explicit evidence policy.

feature-storefeastmlopsfeature-engineeringreal-time-servingml-platform

Research Foundation: 6 sources (2 official docs, 2 paper, 2 books)

This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.

Version History

v1.0.02/15/2026

Initial version

Prerequisites

Use these skills first for best results.

Feature Engineering StrategistGold

Works well with

Feature Engineering StrategistGold Kafka Streaming ArchitectGold MLOps Platform EngineerGold Real-Time Feature Serving ExpertGold Streaming Analytics SpecialistGold

Need more depth?

Specialist skills that go deeper in areas this skill touches.

Feature Store Consistency EngineerGold Real-Time Feature Serving ExpertGold

Common Workflows

ML Platform Infrastructure Setup

Complete ML infrastructure build from feature design through production monitoring

Feature Engineering Strategist→feature-store-architect→MLOps Platform Engineer→drift-monitoring-pipeline-designer

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