DIVI MOUNICA

Results-driven Data Engineer with eight years of experience in designing and building scalable, cloud-native data pipelines. Proven expertise in transforming raw data into reliable, production-ready datasets using modern data engineering tools and cloud platforms. Adept at leveraging Python, AWS (S3, Lambda, SQS), Snowflake, DBT, and Airflow to create efficient, automated data workflows. Passionate about continuous learning, and quickly applying new technologies and techniques to solve real-world data challenges. Known for combining technical depth with a pragmatic, hands-on approach to deliver high-impact, end-to-end data solutions.

• Skilled in data wrangling and transformation, with a strong ability to structure raw, unorganized data into clean, analytical formats.
• Extensive experience in designing and building scalable, end-to-end ETL pipelines — from data extraction to publishing refined datasets to final reporting layers.
• Automated repetitive and ad-hoc manual tasks, significantly improving efficiency and reducing operational overhead.
• Developed custom Git workflows and ensured seamless CI/CD integration for data pipelines and dbt deployments.
• Implemented key-pair based authentication across platforms like Snowflake, dbt, and Airflow to enhance data pipeline security.
• Strong understanding of the modern data ecosystem, with hands-on knowledge of Apache Spark, Kafka, and distributed data processing frameworks.