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Senior Big Data/aws Cloud Architect Resume

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Mclean, VA

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SUMMARY:

  • A visionary technologist with 20 years of rich and diverse technology experience.
  • Extensive experience in Big Data and Hybrid Cloud (AWS) solutions.
  • Crisp focus on achieving business goals and ROI.

PROFESSIONAL EXPERIENCE:

Senior Big Data/AWS Cloud Architect

Confidential, McLean, VA

Responsibilities:

  • Designed the overall architecture of the system (batch/real - time ingestion, data layer, and the API layer).
  • Worked with majority of the AWS services (VPC, S3, Lambda, CloudFormation, Route53, CloudFront, Step Functions, X-Ray, SQS, EMR, Athena, DataPipeline, Kinesis, CloudWatch, Cognito, CloudTrail, IAM, EC2, RDS, SNS, ASG, ELB, and Elasticsearch).
  • Architected and implemented DynamoDB (NoSQL managed service from AWS) for bank’s core systems holding approximately 3 billion transactions. Involved in all aspects of DynamoDB, such as designing tables, keys, indexes, throughput settings, performance testing, etc.
  • Worked with AWS to implement the client-side encryption (using the KMS service) as DynamoDB does not support at rest encryption at this time.
  • Architected and implemented event based system to process bank transaction files as they arrive in S3 from the core systems (S3->SNS->Lambda->EC2->DynamoDB).
  • Implemented DynamoDB streams with Lambda to send real-time alerts via SNS (for certain transactions) and index data in AWS Elasticsearch.
  • Created monitoring setup for application logs and other statistics using CloudWatch Logs and ELK stack. Created dashboards in Kibana (ELK) for all the event based processing.
  • Created CloudFormation templates for majority of the infrastructure.
  • Evolved the solution from one region to multi-region (N. Virginia and Oregon).
  • Setup DynamoDB backups using DataPipeline and EMR.
  • Worked with the DynamoDB service team closely and provided them feedback on DynamoDB and also worked with them on testing new features.
  • Created an Elasticsearch (using AWS ES service) engine for customer transactions indexed in real-time via DynamoDB streams. Also, created an AngularJS application to perform suggest and autocomplete features.

Senior Lead Technologist/Lead Associate

Confidential, Herndon, VA

Responsibilities:

  • Deployed and configured Cloudera Hadoop clusters in several environments.
  • Created geo-visualizations using Tableau.
  • Worked with the Search (Solr) team to assist in moving from single Solr instance to SolrCloud and also use HDFS as the storage layer for Solr.
  • Automated Cloudera cluster installation using Cloudera’s Python API, Puppet, Cobbler, etc
  • Implemented Kerberos authentication in a development Cloudera cluster.
  • Improved performance of MapReduce jobs by tuning configuration changes.
  • Collaborated with the Booz Allen’s cloud provisioning team on capacity planning and sizing of nodes (masters and slaves) for an AWS cluster.
  • Deployed open source Hadoop ecosystem (i.e HDFS, MapReduce, Accumulo, ZooKeeper, NetOwl, SolrCloud, Nagios, Ganglia, Tika, Pentaho, etc) on a fifty node cluster on Amazon Web Services (AWS) and on a bare metal cluster in-house using Puppet.
  • Reduced deployment of cluster of on any size from months to days by automating almost all the manual tasks in Puppet.
  • Performed end-to-end testing of the product. This includes ingestion of unstructured data (emails, text file, PowerPoints, MS Word documents, news feeds, etc) and structured data (RDBMS) into Accumulo. The data in Accumulo is processed for entity extraction by NetOwl. Finally, the data is indexed in Solr for later consumption by end user.
  • Created the architecture and design document of the cluster.
  • Automated administrative tasks of Amazon’s cloud using Amazon’s API and Perl.
  • Created MapReduce jobs to split compressed Wikipedia archive into individual articles (approximately 5 million articles) and cleaned up articles for ingestion into the cluster.
  • Deployed Cloudera several times to small, medium and large clusters using Parcel and RPM deployment methods.
  • Researched on converting existing custom data processing pipeline to Storm.
  • Explored/analyzed data to perform predictive analytics, using Regression and other techniques/algorithms, to predict future events using R.
  • Created interactive applications using R Shiny in R Studio.
  • Managed a team that developed a product to be used by financial institutions to screen applications for credit. The product uses Kafka for queuing credit applications and Storm to process applications by contacting different API to screen information provided in the applications and assign confident scores to each application.

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