[{"content":"Context This project showcases advanced SQL work on public datasets available in BigQuery.\nDemonstrated skills Window functions: ROW_NUMBER, RANK, LAG, LEAD, SUM OVER Recursive and non-recursive CTEs Query optimization: EXPLAIN, partitioning, clustering Advanced aggregations: GROUPING SETS, ROLLUP Anti-joins and correlated subqueries Tech stack SQL · BigQuery · Google Cloud Platform\nResults (To be completed when the project is fully published)\nView on GitHub\n","permalink":"https://paulafonte.fr/en/portfolio/sql-showcase/","summary":"Showcase of advanced SQL skills through CTEs, window functions, and query optimization on public BigQuery datasets.","title":"SQL Showcase — Advanced queries on public datasets"},{"content":"Context This project covers the design of a complete data pipeline on Google Cloud Platform, from ingestion to visualization.\nArchitecture Public API -\u0026gt; Cloud Function -\u0026gt; Cloud Storage (raw) -\u0026gt; Dataflow (transformation) -\u0026gt; BigQuery (analytics) -\u0026gt; Looker Studio (dashboard) Orchestration: Apache Airflow (scheduling, dependencies, alerting)\nDemonstrated skills Data ingestion from a REST API Structured storage in Cloud Storage Transformation and loading into BigQuery Task orchestration with Airflow Dashboard exposure layer Tech stack Python · GCP · BigQuery · Cloud Storage · Dataflow · Airflow · Looker Studio\nResults (To be completed when the project is fully published)\nView on GitHub\n","permalink":"https://paulafonte.fr/en/portfolio/pipeline-etl-gcp/","summary":"End-to-end pipeline with public API ingestion, BigQuery transformation, Airflow orchestration, and dashboard exposure.","title":"ETL pipeline on GCP — Automated ingestion and transformation"},{"content":"Context This project connects my background in applied mathematics with data engineering to solve a concrete forecasting and anomaly detection problem.\nApproach Exploratory analysis and data preparation Feature engineering from multiple sources Modeling with Scikit-learn Evaluation and interpretation of results Visualization of predictions and detected anomalies Demonstrated skills Advanced statistics: hypothesis testing, time series Machine learning: supervised and unsupervised models Mathematical modeling: rigorous approach grounded in my academic background Data storytelling: turning results into operational recommendations Tech stack Python · Pandas · Scikit-learn · Matplotlib · SQL\nResults (To be completed when the project is fully published)\nView on GitHub\n","permalink":"https://paulafonte.fr/en/portfolio/analyse-predictive/","summary":"Predictive models combining weather, sensor, and business signals, with a mathematical approach applied to real operational questions.","title":"Predictive analytics — Demand forecasting and anomaly detection"},{"content":"Background I am Paula Fonte, a data engineer with a background that combines mathematical rigor with practical data delivery.\nAfter studying mathematics at the University of Havana, I continued in France with a Master\u0026rsquo;s degree in Mathematics and Applications at Paris Dauphine-PSL, followed by a Master\u0026rsquo;s degree in Data Engineering at DSTI.\nFor two years, I worked as a data engineer in an environmental technology company, managing the full data chain: from centralizing heterogeneous sources on Google Cloud Platform to building Power BI dashboards for leadership teams.\nIn parallel, I also contributed to research work in mathematical modeling on multilayer graphs and sentiment analysis.\nWhat sets me apart The combination of mathematics, data engineering, and information clarity is still rare. I do not only build pipelines: I also think about how analytical models stay understandable, trustworthy, and useful in day-to-day operations.\nTechnical skills Area Technologies Languages Python, SQL, C++ Cloud GCP (BigQuery, Cloud Storage, Dataflow, Cloud Run) Orchestration Apache Airflow, Docker BI \u0026amp; Visualization Power BI, Looker Studio, Matplotlib Data Science Pandas, Scikit-learn, mathematical modeling Tools Git, GitHub, Linux Languages French: professional working level English: advanced Spanish: native ","permalink":"https://paulafonte.fr/en/about/","summary":"\u003ch2 id=\"background\"\u003eBackground\u003c/h2\u003e\n\u003cp\u003eI am Paula Fonte, a data engineer with a background that combines mathematical rigor with practical data delivery.\u003c/p\u003e\n\u003cp\u003eAfter studying mathematics at the University of Havana, I continued in France with a Master\u0026rsquo;s degree in Mathematics and Applications at Paris Dauphine-PSL, followed by a Master\u0026rsquo;s degree in Data Engineering at DSTI.\u003c/p\u003e\n\u003cp\u003eFor two years, I worked as a data engineer in an environmental technology company, managing the full data chain: from centralizing heterogeneous sources on Google Cloud Platform to building Power BI dashboards for leadership teams.\u003c/p\u003e","title":"About"},{"content":"Do you have a data project, a freelance mission, or simply want to start a conversation?\nYou can reach me here:\nEmail: paulafonte97@gmail.com Phone: +33 6 16 61 01 16 LinkedIn: linkedin.com/in/paulafonte GitHub: github.com/PaulaF-source Location: Paris, Île-de-France — available on-site and remote Availability I am available for freelance missions in data engineering, analytics, and predictive modeling. Short and long missions are both possible.\n","permalink":"https://paulafonte.fr/en/contact/","summary":"\u003cp\u003eDo you have a data project, a freelance mission, or simply want to start a conversation?\u003c/p\u003e\n\u003cp\u003eYou can reach me here:\u003c/p\u003e\n\u003chr\u003e\n\u003cul\u003e\n\u003cli\u003e\u003cstrong\u003eEmail\u003c/strong\u003e: \u003ca href=\"mailto:paulafonte97@gmail.com\"\u003epaulafonte97@gmail.com\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003ePhone\u003c/strong\u003e: +33 6 16 61 01 16\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eLinkedIn\u003c/strong\u003e: \u003ca href=\"https://linkedin.com/in/paulafonte\"\u003elinkedin.com/in/paulafonte\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eGitHub\u003c/strong\u003e: \u003ca href=\"https://github.com/PaulaF-source\"\u003egithub.com/PaulaF-source\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003e\u003cstrong\u003eLocation\u003c/strong\u003e: Paris, Île-de-France — available on-site and remote\u003c/li\u003e\n\u003c/ul\u003e\n\u003chr\u003e\n\u003ch3 id=\"availability\"\u003eAvailability\u003c/h3\u003e\n\u003cp\u003eI am available for freelance missions in data engineering, analytics, and predictive modeling. Short and long missions are both possible.\u003c/p\u003e","title":"Contact"},{"content":"I focus on three complementary service areas, shaped around pipeline reliability, analytical clarity, and automation.\nData Engineering on GCP For teams that need to centralize fragmented data sources and make them easier to operate.\nConnect APIs, files, ERP, or operational tools into a structured data flow Build ETL pipelines for ingestion, transformation, and loading Organize and optimize storage on BigQuery Orchestrate recurring jobs with Airflow Stack: GCP, BigQuery, Cloud Storage, Dataflow, Cloud Run, Airflow, Docker, Python, SQL\nAnalytics and Reporting Foundations For teams that have data but still lack a clear and reliable analytical layer.\nModel SQL tables around business logic and KPIs Prepare reporting foundations for dashboards and recurring analysis Clarify definitions so indicators stay consistent over time Support operational, logistics, commercial, or marketing analysis Stack: SQL, BigQuery, SQL Server, Power BI, Looker Studio, Python\nAutomation for Data Workflows For teams that spend too much time on repetitive updates, synchronizations, or manual checks.\nAutomate recurring data tasks with Python and cloud services Reduce manual work in operational reporting flows Add monitoring and control points when needed Deliver workflows that are easier to maintain over time Stack: Python, Cloud Run, BigQuery, SQL, lightweight orchestration\nEngagement Availability Immediate Location Paris, on-site or remote in France Working languages French, English, Spanish Mission length From one month Interested in discussing a mission? Get in touch →\n","permalink":"https://paulafonte.fr/en/services/","summary":"\u003cp\u003eI focus on three complementary service areas, shaped around pipeline reliability, analytical clarity, and automation.\u003c/p\u003e\n\u003chr\u003e\n\u003ch2 id=\"data-engineering-on-gcp\"\u003eData Engineering on GCP\u003c/h2\u003e\n\u003cp\u003eFor teams that need to centralize fragmented data sources and make them easier to operate.\u003c/p\u003e\n\u003cul\u003e\n\u003cli\u003eConnect APIs, files, ERP, or operational tools into a structured data flow\u003c/li\u003e\n\u003cli\u003eBuild ETL pipelines for ingestion, transformation, and loading\u003c/li\u003e\n\u003cli\u003eOrganize and optimize storage on BigQuery\u003c/li\u003e\n\u003cli\u003eOrchestrate recurring jobs with Airflow\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eStack\u003c/strong\u003e: GCP, BigQuery, Cloud Storage, Dataflow, Cloud Run, Airflow, Docker, Python, SQL\u003c/p\u003e","title":"Services"}]