01/Intro

New York, NY·Remote·Barcelona, Spain·EU

William Gonzalez

Cloud Architect / Principal Software Engineer.

Building scalable data platforms,

ML systems, and enterprise automation

on Cloud.

[email protected]+1 267 241 6872

Jump to projects→Download résumé↓↓Scroll for the full resume

Scroll

02/About

A practice of cloud, data, and code.

Cloud Architect / Principal Engineer. A decade fluent across the GCP stack — BigQuery, Dataproc, Cloud Composer, Vertex AI, App Engine, Cloud Functions, Terraform, GCS — comfortable wherever the work goes. Host the infrastructure teams depend on, orchestrate 200+ processes daily at ~1 TB, and deploy ML end-to-end. Replace fragile manual workflows with cloud-native systems that cut team time, expand capacity, and stay at competitive cost.

Years

10+

Speedup

1d → <1min

Pipelines

200+/day

Daily ETL

~1 TB

03/Experience

2016 – Present

Where I've shipped.

2026

Cloud Architect / Principal Software Engineer

LS Direct Marketing·New York·2026 – Present

Leading GCP modernization across data, ML, and internal platforms — metadata-driven systems internal teams run themselves.

Lead enterprise GCP modernization — data infrastructure, ML systems, and internal tooling across the company.Enterprise-scale cloud platform ownership
Standardized metadata-driven architectures — business and ops teams change workflow logic without engineering tickets.Self-service ops for non-engineers
Centralized React + Python apps on App Engine + BigQuery — pipeline monitoring, log/error analysis, data validation, metadata control, reporting.One UI replaces a wall of dashboards

2023

Cloud Architect / Principal Software Engineer

Herglez SL·Barcelona, Spain·2023 – 2026

Cloud architecture and automation for enterprise data and cloud-native deployments.

Scalable GCP architectures for enterprise data operations and cloud-native deployments.Production-grade cloud-native platforms
Infra automation and engineering standards — predictable releases, less drift between environments.Predictable, repeatable releases
Cloud platform optimization — scalability, observability, production reliability.Stronger SLOs and operational visibility

2021

Data Scientist, Data Insights Department

LS Direct Marketing·New York·2021 – 2023

Led the company's migration from legacy Alteryx / MySQL to a cloud-native GCP stack — data engineering, ML, reporting, internal apps.

Led company-wide migration from Alteryx / MySQL to cloud- native GCP — Python, BigQuery, Airflow, PySpark, Terraform, Dataproc. POC scaled to production architecture.$100M+ org adopted the proposed stack
Rebuilt ROI reporting end-to-end on Django + BigQuery + Python — on-demand, formatted, no human in the loop.30 min → 20 s per report · 8 h → 2 min company-wide
Automated mover modeling on PySpark + Airflow — parallel training, retraining, and scoring driven by metadata, with imbalance correction built in.100+ client campaigns in parallel · terabytes / week

2020

Analyst, Investment Department

IronHold Capital·New York·2020 – 2021

Statistical and predictive models for investment research.

Python financial models estimating corporate performance across multiple sectors.Models drove sector-level investment calls
Quant research using Bloomberg, FactSet, SEC filings, and alternative data sources.
Equity research reports backed by proprietary models and statistical insight.

2019

Research Assistant, Machine Learning

Temple University·Philadelphia·2019 – 2020

ML research for quantitative finance and deep hedging.

Deep Hedging models with recurrent neural networks to hedge Delta.Novel RNN-based hedging research
ML applications for quantitative finance and hedging strategies.
Predictive modeling on structured + unstructured financial data.

2018

Risk IT Developer

SOLVENTIS A.V. SA·Barcelona, Spain·2018

Financial risk systems and reporting automation.

Automated Reuters data retrieval — Python + Jupyter + SQL Server with Slack alerts, replacing manual workflows.~€60K saved annually
Risk calculation systems in Java, Excel VBA, Wolfram Mathematica, Python — robust, scalable, audited.Production risk engine
Eliminated repetitive financial ops — faster reporting cycles, lower error rate, more analyst time on analysis.Hours of manual work / week recovered

2016

Infrastructure Analyst

Accenture·Barcelona, Spain·2016 – 2017

Banking infrastructure and reporting operations.

Automated reporting cycle with VBA tooling for a major banking client.3 weeks → 1 day
Project manager on the daily GTR project — primary liaison between bank managers and the IT team, weekly reporting to Executive Board.Owned client comms for largest GTR account
Coordinated 8 bank departments to standardize income data from 14 sources into a unified ETL format.14 source systems unified

Career timeline

Scroll or click to advance →

04/Selected projects

Showcase

Things I built.

Enterprise Cloud Modernization Program

gcp, bigquery, airflow, cloud-composer, pyspark, terraform + 12

Company-wide migration from Alteryx / MySQL to a cloud-native GCP stack. Started as a POC, became the production architecture of a $100M+ org.

Cortex

app-engine, react, python, bigquery, mysql, gcs + 16

Single operational interface for DAGs, BigQuery state, logs, and metadata — React on App Engine. Ops teams self-serve without engineering.

Automated Mover Modeling System

machine-learning, pyspark, airflow, metadata-driven, model-orchestration, imbalanced-classification + 2

Metadata-driven ML platform — parallel training, retraining, and scoring of 100s of models on PySpark + Airflow, controlled from a UI.

ROI and QBR Reporting Automation

reporting, automation, roi, qbr, powerpoint, django + 4

ROI reports cut from minutes / hours to seconds. QBR PowerPoint decks built in under a minute.

Projects

Scroll or click to advance →

05/Capabilities

What I work with.

Cloud & Infrastructure

Google Cloud PlatformBigQueryDataprocCloud ComposerApp EngineTerraform

Programming & Frameworks

PythonSQLPySparkDjangoReactTypeScript

Data Engineering

Apache AirflowETL / ELTDistributed ProcessingMetadata-Driven ArchitectureCI/CD

Machine Learning & AI

Scikit-learnTensorFlowVertex AIForecastingRecommendation Systems

Platform Engineering

Internal ToolsPipeline MonitoringData ValidationOperational DashboardsSelf-Service Tooling

06/Education & languages

Foundations.

2018

Temple University - Fox School of Business

Master of Science in Quantitative Finance & Risk Management

Philadelphia, USA·2018 – 2020

GPA: 3.79 / 4.0. Focus areas: Financial Time Series, Asset Pricing, Quantitative Portfolios, Derivatives, and Stochastic Volatility.

2009

University of La Salle

Bachelor of Science in Telecommunications Engineering

Barcelona, Spain·2009 – 2015

Computer Science / Software Engineering foundation with focus areas in programming, mathematics, statistics, physics, algorithms, and systems engineering.

Languages

SpanishNative
CatalanNative
EnglishFluent

Education & languages

Scroll or click to advance →