3X FORWARD ENGINEER

Design Modern
Data Platforms
Faster.

3X Forward Engineer helps teams turn APIs, files, schemas, and source structures into modern data platform designs with production-ready models, DDL, ETL patterns, and implementation blueprints reducing weeks of architecture and modeling effort into draft outputs generated in days.

Platform Build — 6 API specs + 14 CSVs → Snowflake DW

Source Data Discovery & AnalysisComplete

6 APIs · 14 CSVs · 3 Excel schemas · 2 DDLs

Metadata & Relationship InferenceComplete

Graph-based dependency mapping & semantic analysis

Architecture Pattern DesignComplete

Generating Medallion / Kimball / Data Vault layers...

DDL & ETL Code GenerationComplete

Production-ready SQL, Python, Spark & orchestration

LANDING25raw tables

STAGING25cleansed

ANALYTICAL18KPI-aligned

DDL + ETL68scripts

3 - 5 DaysFirst platform blueprint generated

4+ LayersArchitecture, model, pipeline, metadata

25+ YearsData architecture expertise embedded

4+ PlatformsSnowflake, Databricks, Fabric, BigQuery

WITHOUT 3X FORWARD ENGINEER

Architecture Design6+ weeks

Data Modeling4+ weeks

DDL & ETL Development8+ weeks

Metadata Documentation3+ weeks

Architecture ExpertiseScarce

Requirements to Roadmap2+ weeks

KPI-to-model alignmentManual, error prone

WITH 3X FORWARD ENGINEER

Architecture DesignDraft in 3 to 5 days

Data ModelingDraft in 2 to 5 days

DDL & ETL DevelopmentFirst pass in 1 to 2 weeks

Metadata DocumentationGenerated in days

Architecture ExpertiseEmbedded patterns

Requirements to RoadmapRoadmap in days

KPI-to-model alignmentAI-assisted

Problems we solve

Every greenfield data platform project stalls on the same bottlenecks: months of manual architecture design, unclear paths from source data to analytical models, and a shortage of senior architects to make the right decisions. 3X Forward Engineer eliminates them at scale.

Months of Manual Architecture Design

Greenfield warehouse and lakehouse builds consume months of senior architect time on schema, layers, and pipelines. Projects queue while teams with source data wait for a path to production.

Source Data Without a Clear Path

Teams start with API specs, JSON feeds, CSVs, and KPIs but no method to turn raw source into an architected platform. The gap takes months to close manually.

Inconsistent Data Modeling Standards

Inconsistent modeling, naming, and architecture standards across teams. Medallion layers, surrogate keys, SCD handling, and pipeline patterns vary by project. Long-term debt builds up.

Missing Metadata Blocking Design

Missing source metadata blocks accurate analytical layer design and KPI alignment. Weeks in business analyst interviews before architecture work can begin.

DDL and Pipeline Code Consuming 60-70% of Time

Manual DDL, ETL pipelines, and transformation coding consume 60 to 70% of greenfield timelines. The most pattern-driven work in data engineering, still done by hand.

Scarce Architecture Expertise

Few teams have Distinguished-level data architects for platform design and modeling strategy. Architects who know medallion, incremental loads, and best practices for Snowflake, Databricks, Fabric, and BigQuery are scarce.

Key features

3X Forward Engineer combines multi-source input analysis, intelligent metadata inference, and graph-based understanding with Distinguished Architect-grade AI to transform source data specs and KPI requirements into layered architecture, data models, and production-ready code.

Multi-Source Input Analysis

Ingests any source specs: API endpoints, CSV/Excel schemas, JSON, flat files, DDLs, and KPI requirements. Auto-detects structure, data types, cardinality, and relationships across inputs simultaneously.

KPI-Driven Architecture Design

Turns business objectives and KPIs into layered architecture with Medallion, Data Vault, Kimball, or hybrid patterns. Every model, dimension, and transformation supports the dashboards stakeholders need.

Intelligent Metadata Inference

AI infers business meaning, classifications, column descriptions, and semantic relationships from attribute names and data patterns. Every object gets enriched metadata before modeling begins.

Graph-Based Source Understanding

Graph intelligence maps cross-source flows, implicit joins, hidden dependencies, and entity relationships. Disconnected inputs become a structured map grounding landing, staging, and analytical design.

Complete Multi-Layer Architecture

End-to-end: landing (raw ingestion), staging (cleansed), and analytical (KPI-aligned Medallion, Data Vault, or Kimball). Transformation logic, SCD handling, incremental loads, and surrogate keys defined per layer.

Production-Ready Code and DDL Generation

Complete DDL for every layer, ETL code in SQL, PySpark, and Python, data quality scripts, lineage docs, and orchestration templates for Snowflake, Databricks, Fabric, and BigQuery. Platform-specific optimizations built in.

How it works

A multi-stage intelligent pipeline that analyzes, designs, and generates your entire data platform automatically.

Convert Source Specs and KPIs Requirements into Architecture, Data Models, and Code

SOURCE DATA SPECS

3X FORWARD ENGINEER

DELIVERABLES

API Specifications & Endpoints

CSV/Excel Schemas

JSON/Flat Files

Source Database DDLs

Business Objectives & KPIs

Missing Metadata
Manual Architect Effort
Inconsistent Modeling Standards
Months of Design & Build

Multi-Source Input Analysis

Intelligent Metadata Inference

Graph-Based Source Understanding

Architecture Pattern Design

Complete Layer Design

Production-Ready Code Generation

Layered Architecture Design with Data Models

Production-Ready DDL & ETL Code

Medallion/Data Vault/Kimball Models

Distinguished Architect-Level Solution

ETL Pipeline Code (SQL / PySpark / Python)

Data Quality Validation Scripts & Lineage Documentation

Target platforms

Code and schemas generated specifically for your target platform — leveraging platform-specific features and best practices.

Snowflake

SQL, Snowpark, stages, tasks

✓ TargetCloud DW

Databricks

Spark SQL, Delta Lake, Unity

✓ TargetLakehouse

BigQuery

Standard SQL, BigQuery ML

✓ TargetCloud DW

Microsoft Fabric

Synapse, OneLake, pipelines

✓ TargetFabric

Success Stories

3X Forward Engineer supports the most in-demand enterprise platform builds. Same AI-powered engine, same quality gates, adapted for each source-to-target platform pair.

Custom accelerator suite architecture showing SI delivery challenges converted into branded in-house tools across the data engagement lifecycle.

US System Integrator Builds In-House Accelerator Suite for 300+ Data Specialists

A data and analytics system integrator wanted to standardize how 300+ specialists produced delivery artifacts across pre-sales and active programs. Technical specifications, estimates, solution designs, project plans, and migration assessments were being created manually with inconsistent quality. 3X Data Engineering helped design and build a fully branded in-house accelerator suite that codified the firm’s delivery methodology and scaled consistent artifact generation across the organization.

Acceleration Advisory

AI-augmented delivery adoption framework for a 60-person fintech data team across six workstreams and five deployed accelerators.

60-Person Fintech Data Team Adopts AI-Augmented Delivery in 12 Weeks

A fintech data engineering organization with 60 people was running six active workstreams using a fully manual delivery model. Requirements, source profiling, technical specifications, code, and documentation were handled by hand, creating delays and quality issues. 3X Data Engineering ran a 12-week acceleration advisory engagement, deployed five accelerators, created role-based playbooks, and certified 15 internal champions so the team could sustain AI-augmented delivery independently.

Acceleration Advisory

Forward engineering architecture showing 48 healthcare source feeds converted into an execution-ready Patient 360 data platform plan.

Patient 360 Platform Planned and Designed in Under One Week

A US healthcare business unit needed to build a Patient 360 analytics platform from 48 source feeds but lacked the architecture, target data models, ETL logic, roadmap, and sponsor-ready artifacts needed to move forward. 3X Data Engineering used forward engineering and metadata intelligence to generate the platform design, Patient 360 data model, ETL scripts, KPI mapping, project plan, and execution-ready canvas in 5 business days.

AI-Augmented Data Engineering Services

Why 3X Forward Engineer

Everything your team needs to design, build, and deploy a modern data platform from source data specs to production-ready code, delivered automatically.

Instant Data Model Generation

Source files and KPI requirements turned into complete dimensional models, Data Vault schemas, or Medallion architectures in hours. Every table, relationship, and grain designed by Distinguished Architect-grade AI.

Production-Ready Code Library

Complete DDL, ETL pipelines (SQL, Python, PySpark), data quality scripts, lineage docs, and deployment templates tailored to source and target. Not boilerplate. Code that deploys on day one.

Embedded Architect Expertise

Distinguished-level architecture knowledge (15+ years equivalent) in every decision: performance, scalability, SCD handling, incremental loads, and partitioning. Senior architect output regardless of team seniority.

KPI-Optimized Data Models

Analytical layers built for specific KPIs. Every fact table, dimension, measure, and grain designed to support reporting and BI from day one. No post-build rework.

Automated Discovery and Assessment

No weeks of source analysis, metadata gathering, or requirement workshops. AI discovery understands source structures, infers context, and maps relationships. Source specs to architecture-ready insights.

Platform-Tailored Implementation

Every schema and pipeline optimized for the target: Snowflake clustering, Databricks Delta Lake, BigQuery partitioning, or Fabric Lakehouse and Warehouse patterns. Platform-specific performance, not generic output.

See Forward Engineer in Action

Get a personalised walkthrough tailored to your data engineering needs and greenfield platform challenges.

Let's talk scale.

Our team of engineering experts and AI architects is ready to help you accelerate your data modernization journey.

Email

Phone / Text

Headquarters

4000, Barranca Pkwy, Suite 250,
Irvine, CA 92604

Design Modern Data Platforms Faster.

Problems we solve

Months of Manual Architecture Design

Source Data Without a Clear Path

Inconsistent Data Modeling Standards

Missing Metadata Blocking Design

DDL and Pipeline Code Consuming 60-70% of Time

Scarce Architecture Expertise

Key features

Multi-Source Input Analysis

KPI-Driven Architecture Design

Intelligent Metadata Inference

Graph-Based Source Understanding

Complete Multi-Layer Architecture

Production-Ready Code and DDL Generation

How it works

Target platforms

Snowflake

Databricks

BigQuery

Microsoft Fabric

Success Stories

US System Integrator Builds In-House Accelerator Suite for 300+ Data Specialists

60-Person Fintech Data Team Adopts AI-Augmented Delivery in 12 Weeks

Patient 360 Platform Planned and Designed in Under One Week

Why 3X Forward Engineer

Instant Data Model Generation

Production-Ready Code Library

Embedded Architect Expertise

KPI-Optimized Data Models

Automated Discovery and Assessment

Platform-Tailored Implementation

See Forward Engineer in Action

Let's talk scale.

Email

Phone / Text

Headquarters

Design Modern
Data Platforms
Faster.