About Me
With over 10 years in the tech industry, I am a seasoned Senior Data Engineer and Big Data Engineer committed to transforming raw data into actionable insights. Throughout my career, I've been a driving force for innovat…
With over 10 years in the tech industry, I am a seasoned Senior Data Engineer and Big Data Engineer committed to transforming raw data into actionable insights. Throughout my career, I've been a driving force for innovation within startup environments, specializing in cutting-edge technologies, data engineering, programming languages, and cloud solutions. My expertise encompasses crafting robust data architectures and implementing efficient ETL processes. Proficient in Python, Java, and Scala, I've successfully designed scalable solutions using diverse database systems, including both relational (RDBMS) and NoSQL. Cloud platforms such as AWS, Google Cloud, and Azure are familiar territories where I've executed impactful projects. Adept at seamlessly integrating data-driven strategies with business objectives, I've consistently delivered meaningful insights that empower decision-making processes. Thriving in dynamic environments, I exceed evolving demands by leveraging my skills to their fullest potential. As a forward-looking professional, I am poised to continue pushing the boundaries of innovation, contributing to the transformative power of data within the tech ecosystem.
Experience
Senior Data Infrastructure Specialist
<p>Spearheaded a real-time inventory tracking system using Apache Kafka for dynamic stock updates<br>
Developed predictive models in Python, resulting in a reduction in stock-outs<br>
Utilized MongoDB for efficient management of extensive product catalogs<br>
Leveraged Apache Spark for in-depth supply chain data analysis<br>
Designed and implemented an integrated data warehouse using Snowflake<br>
Architected a waste tracking system in Java, enabling real-time monitoring<br>
Integrated sensors and IoT data with Apache Flink, optimizing waste collection routes<br>
Deployed InfluxDB to track waste generation patterns over time<br>
Automated AWS infrastructure scaling using Terraform for enhanced robustness<br>
Introduced a data lakehouse architecture, improving the flexibility of waste data storage</p>
Senior Data Infrastructure Specialist
Spearheaded a real-time inventory tracking
system using Apache Kafka for dynamic stock
updates
Developed predictive models in Python,
resulting in a reduction in stock-outs
Utilized MongoDB for efficient management of
extensive product catalogs
Leveraged Apache Spark for in-depth supply
chain data analysis
Designed and implemented an integrated
Data Integration Engineer
<p>Conceptualized and developed a user health data platform with Apache Kafka streams<br>
Implemented data lakes on Google Cloud Platform for diverse user data<br>
Leveraged Python scripts for ETL processes and Apache Spark's ML libraries<br>
Designed a responsive querying system using advanced SQL techniques<br>
Optimized CRM databases, primarily using PostgreSQL<br>
Integrated real-time customer interaction data using Apache Kafka<br>
Employed Star and Snowflake Schemas for efficient structuring of customer data<br>
Streamlined customer segmentation using clustering techniques in Apache Spark<br>
Automated data integration pipelines using Apache NiFi for timely synchronization</p>
Data Engineer
<p>Developed a document management system with real-time indexing powered by Apache Kafka and Apache Flink<br>
Utilized Parquet for efficient storage and retrieval of large documents<br>
Automated document versioning and backup processes on AWS using CloudFormation<br>
Designed a robust search engine in Python<br>
Integrated OCR capabilities for transforming scanned documents<br>
Led the development of a collaborative platform using WebSockets and Apache Kafka<br>
Facilitated seamless integration of third-party tools using Python scripting for ETL tasks<br>
Engineered a data backup system on Azure Blob Storage<br>
Introduced real-time analytics on collaboration patterns using Apache Spark<br>
Utilized AWS services like Lambda and EC2 for on-demand scalability during peak hours</p>