Solution Architect & Data Specialist

Enterprise data,
engineered to last.

15+ years designing Lakehouse platforms, cloud migrations and governed data architecture — across Colombia, Spain, New Zealand and Australia. Now consulting from Brisbane.

J Alberto Suarez C
0+ Years in enterprise data
0Countries delivered in
0% performance gain achieved
0M+ users supported

What I do

Six ways I help teams
get value from data.

Data Architecture & Governance

Enterprise data strategy, governance frameworks, metadata management and privacy — designed to pass audit and survive growth.

Lakehouse Implementation

Medallion architecture on Databricks and Unity Catalog: bronze ingestion, silver conformance, gold dimensional models.

Cloud Migration

AWS, Azure and Oracle Cloud migrations built on Well-Architected principles — secure, resilient and cost-aware.

Database Engineering

Oracle RAC, Data Guard, Exadata, PostgreSQL and SQL Server — performance tuning, HA design and capacity planning.

Analytics & BI

Power BI architecture, dimensional modelling and self-service enablement so leaders get trusted numbers, fast.

AI-Enabled Automation

Document review, completeness checks and exception handling — AI applied where it removes real administrative load.

Signature architecture

The Medallion
Lakehouse

Bronze ingests raw. Silver conforms and cleans. Gold serves the business. Three layers, one governed catalog — the pattern behind every platform I ship.

GOLD

Dimensional Models

Player & team dimensions, registration facts, invoice facts, executive KPI summaries.

SILVER

Conformed Views

Safe casting, null handling, text cleansing, latest-snapshot dedup, materialized views.

BRONZE

Streaming Ingestion

Auto Loader / cloudFiles, mixed encodings, repeated CSV snapshots, schema evolution.

Tech stack

Tools I reach for.

  • Databricks
  • Unity Catalog
  • PySpark
  • Spark Declarative Pipelines
  • Auto Loader
  • Delta Lake
  • Oracle 19c
  • RAC
  • Data Guard
  • Exadata
  • PostgreSQL
  • SQL Server
  • MySQL
  • AWS
  • Azure
  • Oracle Cloud
  • Power BI
  • Power Query / M
  • Python
  • SQL
  • Terraform
  • Git

From the blog

Notes from the field.

Coming soon
Lakehouse · 8 min

Migrating Power Query M-code to PySpark

What actually breaks when you lift Power BI prep logic into Spark Declarative Pipelines — and the patterns that survive.

Coming soon
Governance · 6 min

Unity Catalog without the chaos

A practical catalog and schema layout that scales past the first three teams who onboard.

Coming soon
Oracle · 10 min

When RAC is the wrong answer

High availability is a requirements conversation, not a product choice. A decision framework.