Production-Ready Blueprints for
Data & AI Teams
A practitioner-built resource hub for data engineers, analytics engineers, data architects, and AI platform teams. Access reusable frameworks, production checklists, design templates, and implementation guides for building reliable, governed, and AI-ready data platforms.
Featured Frameworks
Architecture and operating frameworks you can download and adapt for your organization.
Data Quality Engineering Framework
End-to-end operating framework for data quality in modern DE teams — dimensions, rule taxonomy, execution layers, ownership, escalation paths, and KPI scorecards.
Medallion Lakehouse Architecture
Reference architecture for bronze/silver/gold medallion lakehouse on AWS and Snowflake — zone definitions, ingestion patterns, transformation standards, and consumption SLAs.
AI-Ready Data Platform Framework
Reference framework for building AI-ready data platforms — feature stores, vector/RAG pipelines, LLM governance, model lineage, and MLOps integration patterns.
Architecture & Workflow Templates
DE and AI reference architectures with end-to-end workflow blueprints for design reviews and RFCs.
Modern Data Stack Reference Architecture
End-to-end reference architecture for ingestion, dbt transformation, Snowflake warehouse, Airflow orchestration, and BI consumption — with workflow steps and ownership matrix.
Enterprise RAG Architecture
Production RAG architecture for enterprise knowledge bases — ingestion, chunking, vector retrieval, LLM generation, governance, and evaluation metrics.
Lakehouse Batch Ingestion Workflow
Medallion bronze/silver/gold batch ingestion workflow with quality gates, quarantine paths, and operational runbooks for lakehouse platforms.
Production Templates
SQL, Python, and YAML templates you can plug in and deploy.
dbt Production Fact Model Template
Full incremental dbt fact model with merge strategy, deduplication, anomaly flags, and companion schema test definitions. Replace entity, PK, and column placeholders to bootstrap a production mart.
Airflow Production ETL DAG
Production-grade Airflow DAG with task groups, SQL operators, row-count validation, SLA metrics, retries, and alerting hooks. Plug in connection IDs, cron schedule, and merge SQL for your entity.
Data Quality Rule Engine (SQL)
Parameterized SQL rule engine for freshness, PK uniqueness, and completeness checks. Plug in your database, schema, table, and column names — run as a scheduled observability query or wrap in dbt tests.
Implementation Playbooks
Step-by-step guides for data engineers, architects, and platform teams.
Measuring Data Platform Reliability and Business Value
Define and track metrics that demonstrate data engineering value to the business.
40 min · step-by-step sections
Data Governance for Practitioners
Hands-on governance for practitioners: ownership, classification, access, and catalog practices.
50 min · step-by-step sections
Building Enterprise Data Platforms
Architecture patterns for scalable, governed enterprise data platforms.
70 min · step-by-step sections
What people say
Notes from practitioners who tried the templates and playbooks.
Dropped the pipeline SLA script into our daily checks. We caught a late-arriving feed twice last month before downstream dashboards broke.
Shared the dbt playbook with two new analytics engineers. They picked up staging conventions and test patterns faster than our old wiki doc.
Walked through the lakehouse implementation playbook before our platform RFC. It gave our PM a clear picture of bronze vs gold zones—fewer debates, faster sign-off.
Why this platform exists
Practitioners need reusable frameworks and production templates, not marketing pages.Open Data & AI Engineering Frameworks is a hands-on resource hub for teams building modern data and AI platforms.
Read the full story →- Frameworks for data mesh, quality, governance, and AI platforms
- DE and AI architecture blueprints with workflow templates
- Production templates for SQL, Python, Airflow, Glue, and dbt
- Implementation playbooks with step-by-step guides
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