Data Engineer | Machine Learning Enthusiast | Remote-Ready | Skilled in Python, Airflow, dbt, SQL, & Cloud | Bridging Engineering & Data to Deliver Scalable Solutions
I'm a Data Engineer with a strong foundation in engineering and applied mathematics, now focused on building scalable data pipelines, analytics workflows, and AI/ML applications. With experience across remote teams and global startups, I bring both technical expertise and adaptability to fast-paced environments.
I specialize in Python, SQL, dbt, Airflow, and cloud platforms (GCP, AWS, Snowflake, BigQuery), leveraging these tools to design pipelines, automate workflows, and drive data-informed decision-making. My background as a Mechanical Engineering graduate and former university instructor adds a structured, problem-solving mindset to my tech career.
Currently, I'm passionate about transforming raw data into actionable insights and exploring how machine learning can enhance business workflows. My career goal is to grow into leading data teams and mentoring future consultants—while contributing to startups and organizations that value innovation, efficiency, and collaboration.
This project analyzes 14 years of Stack Overflow Developer Survey data to uncover valuable insights into technology trends, developer experiences, and industry shifts. The analysis covers a wide range of topics, including programming languages, salary distribution, education demographics, job roles, and predictions for future tech trends.
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This project processes and analyzes Amazon sales data to generate insightful metrics and visualizations, including sales performance, return rates, profit margins, and fee analysis.
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This project collects, processes, and analyzes weather data to enable insightful visualizations and trend analysis using modern data tools.
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This project is a collection of coursework from the Machine Learning Zoomcamp, covering various topics in machine learning and data science.
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