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.

Jump to projects→↓Scroll for the full resume

[email protected]+1 267 241 6872

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02/About

A practice of cloud, data, and code.

Cloud Architect and Principal Software Engineer with deep expertise building scalable data platforms, machine learning systems, and enterprise automation solutions on Google Cloud Platform. Experienced designing end-to-end data ecosystems with BigQuery, Airflow, Dataproc, PySpark, Terraform, React, App Engine, and Django, with a record of replacing fragile manual workflows with cloud-native systems that process large-scale data reliably and reduce runtime, cost, and operational overhead.

Years

10+

ROI report

30m → 20s

Daily ETL

~1 TB

Annual savings

€60k+

03/Experience

2016 – Present

2026

Cloud Architect / Principal Software Engineer

LS Direct Marketing·New York·2026 – Present

Leading enterprise-scale cloud modernization and platform engineering initiatives across data infrastructure, machine learning, and internal tooling.

Standardized metadata-driven architectures that let internal teams manage complex workflows without direct engineering intervention.Reduced engineering dependency for workflow changes
Lead cloud modernization and platform engineering initiatives across GCP data infrastructure, machine learning systems, and internal operational tooling.
Built centralized cloud-native applications with React, Python, App Engine, BigQuery, MySQL, GCS, and GCP services for pipeline monitoring, log analysis, cloud process management, reporting, validation, and operational insights.

2023

Cloud Architect / Principal Software Engineer

Herglez SL·Barcelona, Spain·2023 – 2026

Designed scalable cloud architectures and automated systems for enterprise data operations and cloud-native application deployment.

Designed scalable cloud architectures and automation systems for enterprise data operations and cloud-native application deployment.
Implemented infrastructure automation and standardized engineering practices to improve deployment reliability and team execution.
Led cloud platform optimization initiatives focused on scalability, operational visibility, and reliable delivery across production environments.

2021

Data Scientist, Data Insights Department

LS Direct Marketing·New York·2021 – 2023

Initiated and led the transition from legacy Alteryx and MySQL workflows to a scalable GCP ecosystem spanning data engineering, machine learning, reporting, and internal applications.

Initiated and led the company's transition from legacy Alteryx and MySQL workflows to a cloud-native ecosystem using Python, BigQuery, Airflow, PySpark, Terraform, Dataproc, and GCP services.Drove company-wide adoption in a $100M+ organization
Developed large-scale ETL pipelines orchestrated through Airflow, Dataproc, and PySpark to process terabytes of data daily.Processed terabytes of data daily
Reduced ROI reporting from 30 minutes to about 20 seconds per report and from 8 hours to about 2 minutes for company-wide execution.30 minutes to ~20 seconds; 8 hours to ~2 minutes

2020

Analyst, Investment Department

IronHold Capital·New York·2020 – 2021

Developed statistical and predictive models for investment research and corporate performance analysis.

Developed statistical and predictive financial models in Python to evaluate corporate performance across multiple sectors.
Conducted quantitative research using Bloomberg, FactSet, SEC filings, and alternative financial datasets.
Produced investment research reports supported by proprietary analytical models and statistical insights.

2019

Research Assistant, Machine Learning

Temple University·Philadelphia·2019 – 2020

Researched machine learning applications for quantitative finance and hedging strategies.

Researched machine learning applications for quantitative finance and hedging strategies.
Developed Deep Hedging models using recurrent neural networks.
Worked with structured and unstructured financial datasets to evaluate predictive modeling approaches.

2018

Risk IT Developer

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

Developed and automated financial risk systems and operational reporting workflows.

Developed financial risk calculation systems using Java, Excel VBA, Wolfram Mathematica, and Python.
Designed automated Reuters data retrieval systems that reduced manual operational effort and saved approximately EUR 60K annually.Saved approximately EUR 60K annually
Led automation initiatives that eliminated repetitive financial operations and improved reporting efficiency.

2016

Infrastructure Analyst

Accenture·Barcelona, Spain·2016 – 2017

Managed reporting and infrastructure operations for large banking clients.

Managed reporting and infrastructure operations for large banking clients.
Reduced operational reporting cycles from three weeks to one day through process automation and VBA tooling.Reporting cycle reduced from three weeks to one day
Coordinated data standardization efforts across multiple banking departments and ETL systems.

Career timeline

2026Cloud Architect / Principal Software Engineer·LS Direct Marketing
2023Cloud Architect / Principal Software Engineer·Herglez SL
2021Data Scientist, Data Insights Department·LS Direct Marketing
2020Analyst, Investment Department·IronHold Capital
2019Research Assistant, Machine Learning·Temple University
2018Risk IT Developer·SOLVENTIS A.V. SA
2016Infrastructure Analyst·Accenture

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04/Selected projects

Showcase

Enterprise Cloud Modernization Program

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

Company-wide modernization from legacy Alteryx and MySQL workflows to a cloud-native GCP ecosystem using Python, BigQuery, Airflow, PySpark, Terraform, Dataproc, Cloud Composer, GCS, CI/CD, and metadata-driven automation. Started as a proof of concept and became the architecture used to scale data processing, reduce runtime and cost, and support self-service operations across the business.

Cortex

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

End-user App Engine application built with React, Python, BigQuery, MySQL, GCS buckets, Airflow, and GCP services that connects DAGs, metadata, BigQuery processes, MySQL state, logs, errors, and pipeline status into a single operational interface. Gives internal users real-time messages, real-time tracking, process snapshots, monitoring views, data checks, reporting utilities, and metadata controls so they can manage complex cloud workflows without engineering intervention.

Automated Mover Modeling System

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

Metadata-driven machine learning infrastructure supporting parallel model training, retraining, and scoring across large client portfolios with PySpark, Airflow, imbalance correction, and automated orchestration.

ROI and QBR Reporting Automation

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

Automated reporting systems that reduced ROI report generation from minutes or hours to seconds and produced fully formatted QBR PowerPoint reports in under one minute.

Projects

01Enterprise Cloud Modernization Program
02Cortex
03Automated Mover Modeling System
04ROI and QBR Reporting Automation

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05/Capabilities

What I work with.

Cloud & Infrastructure

Google Cloud PlatformBigQueryDataprocCloud ComposerVertex AICloud FunctionsCloud SchedulerApp EngineGoogle Cloud StorageAWS S3TerraformJenkinsGitHubCI/CDLinuxIAMCloud Governance

Programming & Frameworks

PythonSQLBigQuery SQLPostgreSQLMySQLSQL ServerPySparkDjangoReactJavaScriptHTMLCSSAJAXPHPJavaCC++RSASMATLABExcel VBA

Data Engineering & Analytics

Apache AirflowETLELTDistributed Data ProcessingMetadata-Driven ArchitectureData SynchronizationBatch ProcessingReal-Time ProcessingTableauFinancial EconometricsTime Series Analysis

Machine Learning & AI

Scikit-learnTensorFlowKerasPyTorchForecastingRecommendation SystemsImbalanced ClassificationAutomated RetrainingAutomated ScoringNeural NetworksRandom ForestsEnsemble Models

Platform Engineering

Internal ToolsPipeline MonitoringLog AnalysisError AnalysisData ValidationReporting AutomationOperational DashboardsMetadata ManagementDeployment StandardsReusable Libraries

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.

University of La Salle

Bachelor of Science in Telecommunications Engineering

Barcelona, Spain

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

Languages

SpanishNative
CatalanNative
EnglishFluent

Education & languages

2018Temple University - Fox School of Business
--University of La Salle
--Languages

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