Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

I am a data engineer/analyst with extensive experience designing and optimizing large-scale data pipelines, real-time streaming solutions, and cloud-based analytics platforms across AWS, Azure, and GCP. I am proficient with Apache Spark (PySpark, Scala, Spark-SQL), Kafka, Databricks, Snowflake, BigQuery, Redshift, and modern ETL/ELT tooling including Airflow, dbt, AWS Glue, and Azure Data Factory. I excel at data modeling, performance tuning, and building event-driven architectures to support fraud detection, customer analytics, and operational intelligence. I enjoy turning data into actionable insights through dashboards in Power BI, Tableau, and Looker, and I integrate ML models using TensorFlow, Scikit-learn, and cloud ML platforms. I have a proven track record of reducing ETL processing times, boosting query performance, modernizing legacy data systems, and delivering real-time insights for enterprise clients in finance, aviation, and digital payments. I thrive in cross-functional teams and continuously seek opportunities to optimize data governance, lineage, and governance practices while delivering measurable business impact.…I am a data engineer/analyst with extensive experience designing and optimizing large-scale data pipelines, real-time streaming solutions, and cloud-based analytics platforms across AWS, Azure, and GCP. I am proficient with Apache Spark (PySpark, Scala, Spark-SQL), Kafka, Databricks, Snowflake, BigQuery, Redshift, and modern ETL/ELT tooling including Airflow, dbt, AWS Glue, and Azure Data Factory. I excel at data modeling, performance tuning, and building event-driven architectures to support fraud detection, customer analytics, and operational intelligence. I enjoy turning data into actionable insights through dashboards in Power BI, Tableau, and Looker, and I integrate ML models using TensorFlow, Scikit-learn, and cloud ML platforms. I have a proven track record of reducing ETL processing times, boosting query performance, modernizing legacy data systems, and delivering real-time insights for enterprise clients in finance, aviation, and digital payments. I thrive in cross-functional teams and continuously seek opportunities to optimize data governance, lineage, and governance practices while delivering measurable business impact.

Jenny Yonjan Tamang

Front-End Developer, Full Stack Developer, DevOps Developer, +3





I am a data engineer/analyst with extensive experience designing and optimizing large-scale data pipelines, real-time streaming solutions, and cloud-based analytics platforms across AWS, Azure, and GCP. I am proficient with Apache Spark (PySpark, Scala, Spark-SQL), Kafka, Databricks, Snowflake, BigQuery, Redshift, and modern ETL/ELT tooling including Airflow, dbt, AWS Glue, and Azure Data Factory. I excel at data modeling, performance tuning, and building event-driven architectures to support fraud detection, customer analytics, and operational intelligence. I enjoy turning data into actionable insights through dashboards in Power BI, Tableau, and Looker, and I integrate ML models using TensorFlow, Scikit-learn, and cloud ML platforms. I have a proven track record of reducing ETL processing times, boosting query performance, modernizing legacy data systems, and delivering real-time insights for enterprise clients in finance, aviation, and digital payments. I thrive in cross-functional teams and continuously seek opportunities to optimize data governance, lineage, and governance practices while delivering measurable business impact.…I am a data engineer/analyst with extensive experience designing and optimizing large-scale data pipelines, real-time streaming solutions, and cloud-based analytics platforms across AWS, Azure, and GCP. I am proficient with Apache Spark (PySpark, Scala, Spark-SQL), Kafka, Databricks, Snowflake, BigQuery, Redshift, and modern ETL/ELT tooling including Airflow, dbt, AWS Glue, and Azure Data Factory. I excel at data modeling, performance tuning, and building event-driven architectures to support fraud detection, customer analytics, and operational intelligence. I enjoy turning data into actionable insights through dashboards in Power BI, Tableau, and Looker, and I integrate ML models using TensorFlow, Scikit-learn, and cloud ML platforms. I have a proven track record of reducing ETL processing times, boosting query performance, modernizing legacy data systems, and delivering real-time insights for enterprise clients in finance, aviation, and digital payments. I thrive in cross-functional teams and continuously seek opportunities to optimize data governance, lineage, and governance practices while delivering measurable business impact.

Available to hire

I am a data engineer/analyst with extensive experience designing and optimizing large-scale data pipelines, real-time streaming solutions, and cloud-based analytics platforms across AWS, Azure, and GCP. I am proficient with Apache Spark (PySpark, Scala, Spark-SQL), Kafka, Databricks, Snowflake, BigQuery, Redshift, and modern ETL/ELT tooling including Airflow, dbt, AWS Glue, and Azure Data Factory. I excel at data modeling, performance tuning, and building event-driven architectures to support fraud detection, customer analytics, and operational intelligence.

I enjoy turning data into actionable insights through dashboards in Power BI, Tableau, and Looker, and I integrate ML models using TensorFlow, Scikit-learn, and cloud ML platforms. I have a proven track record of reducing ETL processing times, boosting query performance, modernizing legacy data systems, and delivering real-time insights for enterprise clients in finance, aviation, and digital payments. I thrive in cross-functional teams and continuously seek opportunities to optimize data governance, lineage, and governance practices while delivering measurable business impact.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

Data Engineer / Data Analyst at PayPal

September 1, 2022 - Present

Collaborated with business stakeholders to translate analytical requirements into scalable data solutions that improved customer insights, operational reporting, and decision-making. Worked with cross-functional teams to design analytics workflows for predictive modeling, customer segmentation, anomaly detection, and performance tracking. Analyzed high-volume transactional data with Spark, Azure Databricks, and Spark-SQL to deliver real-time customer behavior insights. Optimized Azure Data Factory pipelines, contributing to a 50% reduction in ETL processing time. Implemented real-time fraud detection and network anomaly monitoring using Spark Streaming and Kafka on Azure HDInsight. Improved Snowflake OLAP/OLTP models to boost query performance by 45%. Migrated legacy MapReduce workloads to Spark (Scala, PySpark). Automated ML model retraining with Airflow, supporting CLV, churn, and forecasting analytics. Integrated outputs from TensorFlow and Scikit-learn into analytical pipelines and

Data Engineer / Data Analyst at American Airlines

October 1, 2020 - August 1, 2022

Collaborated with stakeholders to gather requirements and design scalable data solutions for flight operations, customer analytics, and revenue management. Developed Spark applications on AWS EMR to process high-volume transactional data, enabling real-time insights into customer behavior and flight performance. Implemented dbt and efficient data structures in Spark and Snowflake to optimize ETL and data retrieval. Designed data pipelines with GCP Dataflow, reducing ETL execution time for flight operations and revenue data. Built real-time streaming pipelines with Spark Streaming and Kafka on AWS MSK for event-driven applications like delay prediction and baggage tracking. Optimized BigQuery models for customer analytics dashboards, improving query performance by 42%. Migrated legacy MapReduce programs to Spark (Scala, PySpark) for faster flight log analysis. Automated ML retraining with Airflow on GCP and deployed models on AWS SageMaker for demand forecasting and dynamic pricing. Cre

Data Engineer at Visa

April 1, 2019 - September 1, 2020

Gained requirements to design scalable data solutions for processing high-volume payment transactions while adhering to security and compliance standards. Developed ETL pipelines with Spark (PySpark/Scala) and optimized real-time fraud detection using Kafka, Spark Streaming, and Apache Flink. Built and automated AWS-based data pipelines with Lambda, API Gateway, S3, and DynamoDB for event-driven fraud monitoring. Integrated merchant, issuer, and cardholder datasets into Lambda and Databricks for real-time financial reporting. Automated AML and compliance monitoring workflows with Airflow, Snowflake, and SQL. Optimized warehouse schemas using Star and Snowflake schemas to reduce query latency. Created interactive dashboards using Looker and Power BI for finance, risk, and fraud teams. Migrated OBIEE reports to Power BI and enhanced ETL for real-time authorization data ingestion. Led CI/CD workflows for cloud deployments, and containerized data applications with Kubernetes.