Results-driven Data Engineer with over 6 years of experience designing and implementing scalable data pipelines, analytics platforms, and cloud-based architectures across AWS, Azure, and GCP. Skilled in Python, SQL, and PySpark, with hands-on expertise in Apache Airflow, DBT, Kafka, and Databricks for end-to-end data orchestration and transformation. Adept at building ETL/ELT workflows, optimizing data performance, and enabling real-time insights through modern warehouses like Snowflake, Redshift, and BigQuery. Experienced in developing BI dashboards using Power BI and Tableau to support data-driven decision-making. Strong foundation in data governance, quality assurance, and CI/CD automation using GitHub Actions, Terraform, and Linux. Passionate about leveraging data and AI to drive business value, improve accessibility, and support innovation in industries such as real estate, finance, and technology. I believe I’m an excellent fit for this Data Scientist role because my background combines strong data engineering expertise with a deep understanding of analytics, machine learning, and real-world problem solving. Over the past six years, I’ve built and deployed scalable ETL pipelines, developed predictive models using tools like Python, Scikit-learn, and TensorFlow, and delivered actionable insights that directly influenced business outcomes. My experience spans cloud platforms (AWS, Azure, GCP) and modern data tools such as DBT, Airflow, and Databricks, giving me the technical depth to manage the entire data lifecycle — from collection and transformation to model deployment and performance monitoring. I’m passionate about turning complex data into meaningful stories that drive smarter decisions, and I thrive in collaborative, data-driven environments where innovation and impact are at the core of the mission.…Results-driven Data Engineer with over 6 years of experience designing and implementing scalable data pipelines, analytics platforms, and cloud-based architectures across AWS, Azure, and GCP. Skilled in Python, SQL, and PySpark, with hands-on expertise in Apache Airflow, DBT, Kafka, and Databricks for end-to-end data orchestration and transformation. Adept at building ETL/ELT workflows, optimizing data performance, and enabling real-time insights through modern warehouses like Snowflake, Redshift, and BigQuery. Experienced in developing BI dashboards using Power BI and Tableau to support data-driven decision-making. Strong foundation in data governance, quality assurance, and CI/CD automation using GitHub Actions, Terraform, and Linux. Passionate about leveraging data and AI to drive business value, improve accessibility, and support innovation in industries such as real estate, finance, and technology. I believe I’m an excellent fit for this Data Scientist role because my background combines strong data engineering expertise with a deep understanding of analytics, machine learning, and real-world problem solving. Over the past six years, I’ve built and deployed scalable ETL pipelines, developed predictive models using tools like Python, Scikit-learn, and TensorFlow, and delivered actionable insights that directly influenced business outcomes. My experience spans cloud platforms (AWS, Azure, GCP) and modern data tools such as DBT, Airflow, and Databricks, giving me the technical depth to manage the entire data lifecycle — from collection and transformation to model deployment and performance monitoring. I’m passionate about turning complex data into meaningful stories that drive smarter decisions, and I thrive in collaborative, data-driven environments where innovation and impact are at the core of the mission.WWWW…