I build reliable data pipelines, streaming data platforms, and lakehouse solutions using AWS and Databricks.
My focus is on turning raw data into trusted, production-oriented data products through ETL/ELT, data quality, distributed processing, orchestration, governance, and CI/CD.
I'm a Data Engineer with a background in Business Analytics, financial auditing & control, and operations, combining business understanding with hands-on data engineering.
I have experience working with:
- Cloud data engineering on AWS and Databricks
- Batch and streaming data pipelines
- Python, SQL, PySpark, and Apache Spark
- Delta Lake and lakehouse architectures
- Data quality and validation
- ETL/ELT and dimensional modeling
- Workflow orchestration
- CI/CD and deployment automation
- Data visualization and operational analytics
I particularly enjoy designing systems where data ingestion, quality, governance, processing, and deployment work together as one platform.
Programming & Scripting Python · SQL · Bash · R · Git · Linux
Data Engineering PySpark · Apache Spark · Spark SQL · ETL/ELT · Data Pipelines · Data Ingestion · Batch Processing · Incremental Processing · Apache Airflow · Delta Lake · Kafka
Cloud & Data Platforms AWS · Amazon S3 · AWS Glue · Amazon Redshift · Amazon Kinesis · AWS IoT Core · Databricks · Snowflake
Data Modeling & Warehousing Dimensional Modeling · Star Schema · OLAP · ERD · 3NF · Data Warehousing
Data Quality & Governance Great Expectations · Data Validation · Data Quality Rules · Unity Catalog · Data Governance
Orchestration & CI/CD Lakeflow Jobs · Databricks Asset Bundles · GitHub Actions · OIDC · Docker
Analytics & Visualization Power BI · Tableau · Databricks SQL · Looker · Pandas · NumPy · Matplotlib · Excel
AI / ML Scikit-learn · TensorFlow · LLM APIs · Generative AI · NLP
- AWS Certified Data Engineer – Associate
- Databricks Certified Data Engineer Associate
- IBM Data Engineering Professional Certificate
- Google Data Analytics Professional Certificate
- dbt Fundamentals
- AWS Cloud Foundations
- Databricks Lakehouse Fundamentals
- IBM Granite Code Optimization
- NVIDIA Generative AI / LLM Training
AWS IoT Core → Kinesis → Databricks → Delta Lake → Unity Catalog → Lakeflow Jobs → GitHub Actions
A near-real-time industrial telemetry platform designed to simulate monitoring of pumps, motors, turbines, pipelines, and storage assets.
The platform demonstrates:
- Python-based industrial sensor simulation
- MQTT telemetry ingestion through AWS IoT Core
- Streaming transport with Amazon Kinesis Data Streams
- Databricks Structured Streaming
- Bronze → Silver → Quarantine → Gold architecture
- Event-time processing and watermarking
- Streaming deduplication
- Data-quality validation
- Invalid-record quarantine
- Asset-health and anomaly aggregation
- Unity Catalog governance
- Lakeflow Jobs orchestration
- Databricks Asset Bundles
- GitHub Actions CI/CD
- GitHub OIDC authentication
- CloudWatch monitoring
- Databricks SQL operational dashboard
🔗 View the Industrial Energy Streaming Data Platform
Python-based ETL pipeline for extracting, transforming, and loading financial data into a relational database.
Airflow-based data pipeline using MySQL and Power BI for music analytics.
NLP-based text classification and sentiment analysis using Python and Scikit-learn.
Containerized Airflow pipeline for automated weather-data ingestion and analytics.
Remote | 2026–Present
Building and supporting data engineering workflows involving:
- Python and PySpark ETL
- API and database ingestion
- Apache Airflow
- SQL
- Snowflake and Amazon Redshift
- Data transformation and validation
- Analytical reporting
Fordham University
Supported database and AI-related academic work involving:
- SQL and relational databases
- Data modeling
- ETL concepts
- Big data technologies
- Python
- Machine learning
- Generative AI and LLM technologies
Worked on data engineering and data-quality projects involving:
- Great Expectations
- Databricks
- PySpark
- Star-schema data modeling
- AWS data services
- ETL/ELT workflows
Applied data analysis and operational reporting to improve business processes and performance monitoring.
M.S. Business Analytics — Fordham University Gabelli School of Business · 2025
Master Technique d'Audit et de Contrôle de Gestion BEM Management School · 2023
M.S. Quality, Hygiene, Safety & Environment Management ISM Dakar
🇺🇸 English — Fluent 🇫🇷 French — Native
- Cloud Data Engineering
- AWS Data Platforms
- Databricks & Lakehouse Architecture
- Streaming Data Engineering
- Data Quality & Governance
- Data Modeling
- Analytics Engineering
- Data Platform Automation
- AI/LLM-enabled Data Engineering
📍 New York, USA
Building data platforms that are reliable, observable, governed, and ready to scale.