Data Engineer | Big Data Engineer: ~7 years----------------------------------• Python, SQL: 9 years----------------------------------• Apache Spark: 3 years• Dbt: 3 years• Snowflake: 3 years• Databricks: 3 years• Apache Kafka: 2 years• Apache Airflow: 2 years----------------------------------• Big Data Technologies (Hive, HBase): 3 years• ETL Processes: 4 years----------------------------------• PowerBI, Tableau, Apache Airflow, Databricks: ~4 years----------------------------------• Remote work: 4 years----------------------------------• AWS (S3, EC2, Lambda, Redshift): 4 years• GCP (Google Cloud Platform): 3 years• Azure: 2 years----------------------------------—• Git, MLflow: 4 years• CI/CD Pipelines (Jenkins, GitHub Actions): 3 years----------------------------------• MySQL, PostgreSQL: 4 years• NoSQL (MongoDB, Cassandra): 2 years• Elasticsearch: 2 years--------------------------------------------------------------------—As a Data Engineer and Data Scientist with 9 years of experience, I've developed an understanding of data handling and analysis, primarily through the use of Python, SQL, and machine learning technologies like TensorFlow. My expertise lies in transforming complex data into actionable insights, leveraging tools like PowerBI and Tableau for visual analytics. My journey in the data realm has been marked by continual learning and application of advanced techniques in machine learning, utilizing libraries like scikit-learn to refine and optimize models.My experience also extends to cloud computing, particularly with AWS, where I've honed my skills in managing and deploying data infrastructure and services. This combination of analytical, technical, and cloud skills enables me to deliver comprehensive data solutions that drive decision-making and business growth.In my role, I focus on the entire lifecycle of data science projects, from data collection and cleaning to model development and deployment. The intersection of data engineering and science has allowed me to not only understand but also to articulate the story behind the data, making it a powerful tool for strategic insights.