Data Platform Architect
Turning fragile data systems into scalable cloud platforms.
SYSTEM STATUS
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Role : Data Platform Architect
Focus : Cloud data platforms, automation, reliability, cost control
Operating : Where architecture meets hands-on execution
Bias : Simple systems, observable pipelines, documented ownership
I build the boring parts of data platforms that companies quietly depend on: ingestion, orchestration, transformations, infrastructure, validation, monitoring, and cost controls.
The goal is not just to make pipelines run. The goal is to make data systems easier to trust, operate, debug, scale, and afford.
legacy scripts -> automated cloud workflows
manual operations -> repeatable runbooks and CI/CD
silent failures -> observable pipelines and checks
expensive warehouses -> tuned queries, storage, and compute
unclear ownership -> maintainable platform boundaries
- Modernized a legacy ML data workflow from private-server scripts into an automated cloud data platform.
- Reduced cloud data platform spend by 30% through warehouse, storage, and infrastructure optimization.
- Supported an enterprise analytics platform consolidating operational, CRM, product, and transaction data across multiple source systems.
- Built marketing and attribution pipelines for analytics and paid-media workflows.
- Designed high-scale data systems processing 50M+ daily events for analytics and machine learning workloads.
| Layer | Tools |
|---|---|
| Cloud | GCP, Azure |
| Warehouses | BigQuery, Snowflake |
| Transformation | dbt, SQL, Python |
| Orchestration | Cloud Run, Cloud Functions, Azure Data Factory, workflows |
| Infrastructure | Terraform, Docker, GKE |
| Reliability | dbt tests, observability, lineage, runbooks, CI/CD |
- Data systems with clear failure modes.
- Pipelines that can be operated by someone other than the original author.
- Cost controls that are designed into the platform, not patched afterward.
- Business logic that is explicit, tested, and documented.
- Infrastructure that supports change without turning every release into a risk event.
I am focused on cloud data platforms for analytics and machine learning, especially systems that have outgrown manual scripts, unclear ownership, or expensive warehouse patterns.
Architecture thinking. Hands-on execution. Reliable data systems.