Solution Architect & Data Specialist

Enterprise data,
engineered to last.

20+ 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.

For football

Data your club can trust on matchday.

I referee on weekends and build registration and compliance data for football clubs through Let's Data Talk. Football data has its own rhythm: seasons, transfers, age groups and volunteers. I design for it.

Clubs

Match, player and membership data in one governed place: registrations that reconcile, rosters coaches can rely on and reporting the board can defend.

Federations

Registration, competition and participation data across every member club, with shared standards, compliance reporting and one source of truth.

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.