Humera Qayyum

About Humera Qayyum

Passionate Engineer with 10+ years of experience in Technology. Had experience working with a number of Devops tools such as AWS, Linux, GIT, Jenkins, JFrog Artifactory, Docker, Kubernetes, Apache Tomcat, Chef, Puppet, Terraform, Ansible. Strong Experience deploying applications in Non-prod environment and production environment, Debugging, Load Balancing, Cloudwatch Monitoring, EBS Volume.ELK Stack (Elasticsearch, Logstash, Kibana)Snowflake, RedshiftInfrastructure As Code : Terraform, Cloud FormationCloud: AWS, GCP. Azure

Experience

1. Aws Data Engineer

   DIRECTV

   Jan 2020 — Present · US

   Deployed infrastructure on AWS utilizing as EC2 (Virtual Servers in the Cloud), RDS (Managed Relational Database Service), VPC and Managed Network and Security, Route 53, Direct Connect, IAM, Cloud Formation, AWS Ropeworks (Automate operations), AWS S3, Glacier (Storage in the cloud) and Cloud Watch Monitoring Management• Used AWS EMR to transform and move large amounts of data into and out of other AWS data storesand databases, such as Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB.• Used Spark SQL for Scala & amp, Python interface that automatically converts RDD case classes toschema RDD.• Import the data from different sources like HDFS/HBase into Spark RDD and perform computationsusing PySpark to generate the output response.• Developed reusable framework to be leveraged for future migrations that automates ETL from RDBMSsystems to the Data Lake utilizing Spark Data Sources and Hive data objects.• Creating Lambda functions with Boto3 to deregister unused AMIs in all application regions to reducethe cost for EC2 resources.• Worked with IAM to set up user roles with corresponding user and group policies using JSON and add project users to the AWS account with multi factor authentication enabled and least privilege permissions.• Utilized AWS CLI to automate backups of ephemeral data-stores to S3 buckets, EBS and create nightly AMIs for mission critical production servers as backups.• Experience with EC2, Cloud Watch, Elastic Load Balancing and managing securities on AWS.• Knowledge Cloud Formation, AWS Ops Works, AWS Elastic Beanstalk.• Used AWS lambda to run code virtually.• Designed ETL pipelines, data extraction, data managing and then we schedule ETL mean data jobs the using airflow• Developed Kibana Dashboards based on the Log stash data and Integrated different source and targetsystems into Elasticsearch for near real time log analysis of monitoring End to End transactions

Education

• Manhattan School of Computer Technology

  Bachelor's degree