John is a highly skilled Data & ML Engineer at Agilytic, known for his technical expertise and passion for data analysis. From his recent experience John excels in creating efficient data pipelines and optimizing data processes to deliver actionable insights. His collaborative approach make him a valuable asset to any team. John is continuously mentored by technical experts at Agilytic, ensuring he learns from the best and stays at the forefront of industry advancements.
💼 Professional experience
Agilytic
Data & ML Engineer Since Jan 2023
Public Foundation
- Data Platform selection and architecture, in collaboration with client team and Agilytic Data Architect.
- Design and implementation of a medallion (bronze-silver-gold) platform on Microsoft Fabric and Azure Databricks, ingesting Unit4, Salesforce, SQL databases, APIs, SharePoint and SFTP sources.
- Set up CI/CD with Azure DevOps and trained the internal teams on PySpark and Databricks for autonomous operation.
- Technologies used: Microsoft Fabric, Azure Databricks, PySpark, Azure DevOps, Power BI, Git.
Retail
- Took over administration of a production data platform after the departure of the client's internal data team, ensuring stability and continuity.
- Monitoring of production pipelines, proactive data-quality checks and incident remediation.
- Automated routine operations and managed the data warehouse supporting business analytics.
- Technologies used: Azure Data Factory, Azure Automation, Azure Analysis Services, Python, PowerShell, Power BI, DAX, SQL (PostgreSQL, MySQL).
Services
- Build and design data pipelines on AWS for a reporting data platform.
- Put in place interconnectivity between different AWS accounts to perform the ETL process.
- Employed a delta strategy for specific tables assigned by the client.
- Implemented CI/CD pipelines on the client's GitLab infrastructure.
- Technologies used: AWS S3, VPC, Secrets Manager, Databricks, PySpark, SQLAlchemy, GitLab CI.
Retail (B2B)
- Developed a lead scoring algorithm to find potential new “good” clients exploiting BNB and BCE data using Scikit-Learn, with scores delivered to the sales teams through Power BI.
Pharmaceutical
- Data pipelines design and implementation of a Data Platform on Azure, provisioned with Terraform, for reporting and advanced analytics use cases.
- Created a webapp using Streamlit for data cleaning with direct interaction with an Azure Database.
- Developed a time series algorithm for sales forecasting using Prophet and Darts.
- Mentored the client's data lead to full autonomy on the platform.
- Technologies used: Azure Data Factory, Azure Data Lake, Databricks, Pyspark, Terraform, Streamlit, Prophet, Darts
N Brown Group
Data Scientist (MSc Placement) June 2022 - Aug 2022
- Developed a Recommender System prototype based on implicit data from purchase data.
- Technologies used: Python, SQL, NumPy, Pandas, Plotly, Scikit‑learn, Matplotlib, Scipy, JupyterLab, AWS Sagemaker, AWS Athena.
🦾 Certifications, trainings
Methodologies
- Data processing, analysis, modelling & visualization
- Product recommendations
- Machine learning
- Clustering and Classification
Software & programming
- Python (incl. Pandas, Numpy, Scipy, Scikit, NLTK)
- Pyspark, Databricks
- SQL
- SageMaker
- MySQL
- Tableau
- Git
Certifications
- Microsoft Certified: Fabric Data Engineer Associate (DP-700)
- Microsoft Certified: Azure Data Engineer Associate (DP-203)
- Databricks Certified Data Engineer Associate
- Astronomer Certification for Apache Airflow 3 Fundamentals
- Power BI Data Analyst Associate
- Academy Accreditation - Databricks Lakehouse Fundamentals
- Create Machine Learning Models in Microsoft Azure – Coursera
- Microsoft Azure Machine Learning for Data Scientists – Coursera
🎓 Academic credentials
- MSc in Data Science Lancaster University, 2022 Distinction
- Data Science Bootcamp BrainStation, 2021 (online)
- Data Science with Python Track Datacamp, 2021
- Bachelor’s in Telematic Systems Engineering USMA, 2020 Cum Laude
🇺🇳 Languages
🇪🇸 Spanish: native
🇬🇧 English: fluent
🇫🇷 French: limited proficiency
🔐 Proprietary and confidential. 💡 Profile CVs are provided for illustration purposes. ✅ Planning of specific experts will be secured upon formal agreement.