(Full-Stack) Software Developer Resume Example

• Engineered solutions for faster Teradata Vantage on AWS and Teradata Do-It-Yourself AWS Marketplace releases.
  Created and tested RPM (RedHat Package Manager) upgrade bundles for Teradata Vantage on AWS. 24/7 Customer
  Product Support for Teradata Do-It-Yourself AWS CloudFormation Provisioning, IntelliCloud AWS
• Vantage on AWS 1.1.6.2, 1.1.7.0, 2.1: Instrumental in releasing Vantage to be generally available for AWS
  customers, specifically for creation of RPM package upgrade bundles for Teradata Database and integration
  testing of UDA (Unified Data Architecture) Applications with database.
  ○ Setup deployment environments for respective versions, upgraded them through TD PUT (Parallel
  Upgrade Tool), and tested integration
  ○ Leveraged AWS CLI and IAM Roles for quicker execution of upgrades
  ○ Demonstrated principle of least privileges in granting access
• Designed and created Jenkins CI/CD pipeline for Teradata Do-It-Yourself AWS CloudFormation Provisioning
  testing. Used draw.io for flowcharting, Cucumber for Behavior Driven Development (BDD). Executes Python
  “pytest” REST API tests on AWS instances from Docker container in Kubernetes cluster. Leveraged
  Terraform for deployments as well.
  ○ Scale In/Scale Out/Scale Up/Scale Down/Resize Volumes: Wrote Python script testing Teradata
  Database horizontal and vertical scaling of AWS instances. e.g. x nodes to y nodes, m5.4xlarge to m5.8xlarge instance type and 10 Terabytes (TB) of Elastic Block Storage (EBS) volumes to 12TB,
  saving 2 hours of time.
  ○ Node Failure Recovery (NFR): Another Python script that tests failure of Teradata system nodes and
  replacement for recovery, saving 1 hour of time.
  ○ Data Stream Utility (DSU): Python scripts that test integration of DSU which consists of the Teradata
  nodes as media servers to leverage Data Mover objects that transfer savesets to S3 buckets and back to
  systems. Passes REST API (GET, POST) requests to configure AWS instances for backup and restore
  jobs. This was tested manually for Vantage on Google Cloud, which took about 1 hour.
  ○ Tests leverage Docker containers for environment configuration management
  ○ With team, migrated from Docker within VMware to Docker within Docker in Kubernetes cluster
  under Test as a Service framework
• Patched sites in pre-production by leveraging DynamoDB to get Lambda associated with site ID, then
  updated CloudFormation Template (CFT) in JSON that deploys site specific Lambdas after deployment of
  upgrade bundles to production S3, jfrog Artifactory, Teradata Software Service (TSS).
• Added NOS (Native Object Store) support for AWS Teradata Database instances by adding necessary
  Python code within codebase that leverages Troposphere Python library for CloudFormation template
  generation in JSON.
• Sent Teradata Database AMI for successful AWS marketplace scan and into private marketplace, ready for
  AWS GovCloud.

Software Engineer (Backup and Restore CI/CD Team)

• Developed, designed, and maintained CI/CD pipelines for release of Teradata products under Backup and Restore
  (BAR) department. Cloud-Agnostic (AWS/Microsoft Azure/GCP) Customer Product Support for Data Stream
  Architecture (DSA). Created Python and Bash scripts that automate and shorten timeframe of software
  development lifecycle. Systems Administration of many Teradata systems in SUSE Linux Enterprise Server
  (SLES), provisioned by VMWare.
• Integrated and customized Hygieia , an Open Source Dashboard from Capital One for monitoring issue metrics,
  Cloud metrics, and healthcheck of Jenkins pipelines. Used Angular.js, Java Spring Boot, HTML/CSS,
  Python, Bash cronjobs, and MongoDB
• Wrote GCP (Google Cloud Platform) Jenkins Image Automation pipeline in Ansible that takes Base OS
  Image (TD Optimized) and installs RPM packages for Data Stream Controller images as UDA (Unified Data
  Architecture) Application of Vantage on Google Cloud
• Architected and implemented DSA-CI/CD-Healthcheck, which is a suite of cron jobs that poll which Teradata
  systems are down, checks Net Backup and Dell Data Domains
• Authored CICD pipelines for move to Postgres for DSC product: Premerge to Master + Post-merge.
  Migrated jobs, provisioned, and configured VMs to be compatible with Postgres
• Created Bash scripts to automate performance metric test jobs (BARsuite) to backup and restore multiple
  Azure Cloud storage accounts, blob containers, prefixes, etc. Auto-generated XMLs with Bash to create jobs
  using CLI for Data Stream Controller (DSC) Teradata UDA App.
• Added features and maintained Pre-Merge to Feature/Master and Post-Merge (Release) pipelines on Jenkins
  and TeamCity.
  ○ Automerge: After tests complete, created Bash + Jenkinsfile scripts to curl GitHub REST API and
  automatically merge feature branches to master. Saved 1-2+ human hours per week from manually
  merging pull requests.
  ○ Cloud + On-Prem Target Groups: Auto-generated XMLs with Bash to configure target groups using
  CLI of Data Stream product with AWS S3, Azure blobs, NetBackup, etc.
  ○ Automated BlackDuck (Security), Coverity, and Sonar checks on release code to auto-generate Confluence Wiki Page of results
  ○ Pipeline enhancements in Python, for example: DBS Control for incremental restore flags

Designed, built, improved, and maintained different test automation frameworks for an international customer-facing, search-engine web application similar to Google. Developed and executed automation scripts for the Search Engine UI frontend and EWS (Excalibur Web Services) backend.

• Completely revamped legacy EWS Stress Test code to introduce full automation. Automated the Java Load App Stress Test, Jupyter Notebook (Python) throughput report creation, and SlackBot/JIRA API using Linux Bash scripts and Cron Jobs. Hits the server with 30 threads per second.
• Kept load times under 300ms per query on the server. 95th percentile latency: ~300ms, mean 196ms
• Caught memory leaks and crashes before backend updates push to production every week
• Used Kubernetes to isolate microservice responses and latency issues.
• Istio's Grafana + PRTG for more latency analysis
• Deployed own version of EWS/QAS for experimentation in a dev environment
• Wrote a Wraith Image Comparison (BBC News) test automation framework from scratch. Created Windows Powershell scripts to copy images on a Network Drive, rename them, and make compatible with Wraith configs.
• Programmed a Cross-Browser test automation framework using Selenium Grid, Docker Zalenium, Powershell, BrowserStack for functional testing.
• 3+ timely builds released per week. Saved smoke testing time by more than 15 hours per week by:
• Fixing the bugs in legacy Java/Selenium based automation framework, and in the Android JUnit Tests.
• Creating Python Selenium scripts to automate end-to-end Kafka validation checks, and other checks depending on nature of release (e.g. Safe Search).
• Regularly maintained and refactored Selenium WebDriver C# and Java Automation Functional, News, and Queries test frameworks for a Search-Engine frontend. Reported bugs from Extent Reports or HTML files.
• Code Reviews with JIRA + Mercurial. Established automation best practices that significantly reduced code review time.
• Service Configuration Management with HashiCorp Consul
• ELK (Elastic Stack) for logging aggregation + White box testing

• Built the frameworks from scratch for Selenium IDE, WebDriver C#/Python Automation testing through JavaScript/HTML web scraping. Used T-SQL temp tables, joins to run QA tests on the database.
• Responsible for Regression, Stress, and Performance Manual and Automation Testing for many BlackBaud Enterprise CRM websites for a University Client base
• Used Object Oriented Design principles and algorithms for clean, modular code that can be used for many automated tests
• Worked with a SDLC in JIRA's Kanban Board with Agile + daily standups. Regression testing on 2 day deliverable turnarounds. Created many Zephyr unit tests in JIRA.
• Helped develop in the Full-Stack and create/update detailed documentation
• Wrote VB.NET programs and helped clean developer code. Tech Stack: Frontend: BBECRM HTML Backend: C#/VB.NET/T-SQL

• Gathered requirements, designed, and developed a routine T-SQL Stored Procedure plus Queries for Database Statistical Analysis with Data Visualization in R and in Excel
• Created a WealthPoint Salary Analysis Screening with Advanced T-SQL Unions, Joins, Temp Tables, etc.
• Wrote a Query for thorough daily Smart Field Quality Assurance regression testing with Advanced Excel VLOOKUPS, Pivot Tables, etc. for effects on Queues

• Kops + Kubernetes + AWS
• Built and deployed Helm Charts with Jenkins (MariaDB) on Kubernetes. Helm Repository on S3.
• Deployed WordPress with Volumes to keep state of MySQL database with EC2, EFS, etc. on AWS
• Deployed Istio sidecars for DNS routing to access microservices and legacy microservices
• Service Discovery, ConfigMaps, Ingress Controllers, Affinity, CRDs, Taints and Tolerations
• Kubeless with Kafka, RBAC with Istio, Distributed Tracing with Jaeger, Istio Grafana Metrics, Canary Deployments, etc.
• Other experience with AWS: Route53 (DNS Hosted Zones), VPCs (Security groups), IAM access key management, etc.
• Terraform + AWS
• Kops for managing clusters, Terraform for provisioning AWS resources not managed by kops
• Saved States, backups of AWS infrastructure with Terraform on S3
• Azure DevOps
• CI/CD pipelines for .NET Core Apps, Java Apps

• SmartFit: Built an iOS Fitness app in Swift 3 with a team that creates customized workouts based on user preferences and shows progress over time. Presented to Angel investors who judged iOS app ideas and execution
• Data Mining: Created projects in Python Beautiful Soup, Scrapy Spider Crawls and in Selenium WebDriver C# (with some JavaScript) to scrape websites by parsing HTML DOM properties with XPath, used the data to test large scale projects and to present trends in charts with Python Matplotlib, and in R Statistical Programming
• Food Smart: At a hackathon, worked with a partner to optimize the College Student diet by creating a web application that calculates the most nutritious foods for the lowest amount of money in dollars. Uses a subset of optimization called Linear Programming, with the Simplex Algorithm. Uses Python Flask backend, HTML/CSS, JavaScript frontend.
• Twitter: Created an iOS app written in Swift 3 that replicates the user interface and functionality of the famous Twitter social media app. Uses an HTTP-based RESTful API.
• Yelp: Created an iOS app that is also written in Swift 3 that replicates the user interface and functionality of the widely known Yelp review app.
• Flicks: Made an iOS app that lists top rated and now playing movies with high resolution poster views of the movies, with movie summaries upon clicking on a movie cell. Functionalities: Infinite scrolling, refresh, search, can display a network error when WiFi is disconnected.
• Cryptography: Created a Huffman Compression program in Java and in C++ that encodes any file into binary sequences into saved data, saving a plethora of bytes and decodes them back to strings. Also created a Caesar Cypher in Java for encryption/decryption methods.
• CoupleTones: (CSE 110 Class Project) Collaborated with a team on an Android app in Java with a Firebase backend called CoupleTones (everyone in the class made this) which tracks and notifies the user whether or not they have reached a favorite location that a friend favorited.
• Auto-Complete: Created an Auto-Complete Program in C++ using data structures such as priority queues, Multi-way Search Trie, and a modified Breadth-First Search (BFS) function. o Functions to auto-complete words in a Graphical User Interface
• Argument Parser: Created a GNU Linux Argument Parser in Java that streamlines commands with options and operands to implement Linux functions. Uses Java Generics, Option, Operand Classes, HashSets, HashMaps, ArrayLists, etc.
• Uniq: Made a program in C that mimics the Unix Utility command unique by creating a database and parsing through it based on a text file o In addition, it returns a list of lines in a file, sorted by the number of times each occurs