Leyla Helin C.

Leyla Helin C.

AnkaraTurkey

Data Mining & Management | AWS Glue, Amazon Web Services, AWS Lambda

Stream and batch processing to extract, transform and load large amount of data while optimizing and maintaining search using Apache Spark, Apache Kafka and Apache Flink in Scala Building API s in Golang and Python Use NewRelic, Kubernetes and Grafana service to maintain, observe and large amount of stream Create job schedules using Apache Airflow DAGs and Gitlab CI/CD pipelines Extract, transform and load large amounts of data from a variety of sources(S3, Redshift, RDS) with pyspark ETL jobs(AWS Glue, AWS EMR) 􏰀 Use best practices to scale Apache Spark jobs and data partitions with AWS Glue 􏰀 Reduce run time and usage memory for existing jobs on pyspark manipulating parameters of spark and AWS Glue(control DPU and execution time) 􏰀 Build large and complex data pipelines that reads and writes different data sources like AWS S3/AWS Redshift/AWS RDS 􏰀 Create daily and on-demand data pipelines using workflows, triggers, AWS Glue and AWS Lambda 􏰀 Control health and errors of AWS Glue jobs using CloudWatch events, AWS Lambda and Slack channels
Leyla Helin C.

Leyla Helin C.

AnkaraTurkey

View profile

Data Mining & Management | AWS Glue, Amazon Web Services, AWS Lambda

Specializes in
Stream and batch processing to extract, transform and load large amount of data while optimizing and maintaining search using Apache Spark, Apache Kafka and Apache Flink in Scala Building API s in Golang and Python Use NewRelic, Kubernetes and Grafana service to maintain, observe and large amount of stream Create job schedules using Apache Airflow DAGs and Gitlab CI/CD pipelines Extract, transform and load large amounts of data from a variety of sources(S3, Redshift, RDS) with pyspark ETL jobs(AWS Glue, AWS EMR) 􏰀 Use best practices to scale Apache Spark jobs and data partitions with AWS Glue 􏰀 Reduce run time and usage memory for existing jobs on pyspark manipulating parameters of spark and AWS Glue(control DPU and execution time) 􏰀 Build large and complex data pipelines that reads and writes different data sources like AWS S3/AWS Redshift/AWS RDS 􏰀 Create daily and on-demand data pipelines using workflows, triggers, AWS Glue and AWS Lambda 􏰀 Control health and errors of AWS Glue jobs using CloudWatch events, AWS Lambda and Slack channels
More than 30 hrs/week