Jasmine C.
Senior Data Engineer
Open to offersNew to PlatformAbout
Jasmine C. is a solution-oriented Data Engineer with seven years of experience in ETL/ELT and Big Data, focusing on the Databricks platform and pipeline design. She has demonstrated expertise in building scalable, fault-tolerant systems using Azure cloud services, especially within multi-source enterprise contexts. Jasmine excels in the Medallion Architecture and Delta Lake transformations, enhancing business intelligence through Power BI. Her role at American Express involves leading the transition of legacy ETL pipelines to cloud-native ELT architectures, supporting millions of transactions in the U.S. Accounts Receivable division. With a focus on Medallion Architecture, she optimizes data analytics and executive reporting by implementing STAR schema models using Delta Lake operations. Jasmine's role at Chewy saw her architect event-driven data pipelines amidst AWS migration, while at Marvell Technology, she refined data handling systems for semiconductor testing. She is proficient in Apache Spark and Python, continually driving data quality governance and CI/CD pipeline advancements.
Experience
Engineer III - Senior Data Engineer
American Express · 2024 — PresentLeading the transformation of legacy ETL pipelines into cloud-native ELT architecture on Databricks for the U.S. Accounts Receivable division. Designed a Fast-Forward operating model for the AR domain, ensuring standards for availability and compliance. Developed a Medallion Architecture (Bronze/Silver/Gold) in Databricks to synchronize ingestion, transformation, and curation for billing and reconciliation analytics. Engineered Azure Data Factory pipelines for multi-source ingestion, protecting critical workflows. Integrated Azure DevOps Git for CI/CD promotion across environments and enhanced loading processes through incremental updates and CDC from Kafka systems. Optimized PySpark pipelines for large-scale dataset processing and collaborated with BI teams to improve dataset design for reporting.Data Engineer - Data
Chewy · 2022 — 2023Contributed to designing and scaling critical data pipelines on the core platform team, focusing on the commerce lifecycle from product discovery to fulfillment. Owned event-driven pipelines that processed high-volume transactions. Developed Scala-based services on AWS EKS for event handling and data processing while implementing Kafka for asynchronous processing. Integrated Snowflake for OLAP functionalities and established CI/CD, orchestration, and observability standards with GitHub Actions and Airflow. Worked cross-functionally to align data workflows with business metrics.Software Engineer
Marvell Technology Associates · 2019 — 2021Operated within the test and validation ecosystem, enhancing data flow between SSD hardware and firmware teams. Developed an automated ETL data pipeline using Python and Linux for telemetry data processing, reducing manual handling efforts. Created log ingestion services using SSH and Python to normalize firmware logs. Built micro-batch processing workflows with Java and Apache Flink for improved ETL throughput. Designed database schemas in PostgreSQL for time-series data storage and automated validation workflows using Jenkins and shell scripting.
Skills & Expertise
Education
- Master of Science in Information SystemsNortheastern University