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Experienced Cloud DevOps Engineer with a decade of hands-on expertise; showcasing a proven ability to conceive, implement, and enhance DevOps methodologies across intricate software development projects. Committed to enhancing scalability, refining procedures, and ensuring continuous integration and delivery for the optimization of organizational efficiency and productivity. Proficient in leveraging cloud computing platforms, specifically Azure, OpenShift stack, and Amazon Web Services (AWS); additional expertise as a Site Reliability Engineer. Skilled in automated configuration, deployment, and orchestration across cloud platforms and data centers. Extensive experience in various DevOps aspects, including CI/CD pipeline management, build/release coordination, and successful implementation of AWS and Azure DevOps. Proficient in code deployment through CI/CD pipelines using Jenkins, Bamboo, VSTS for ADO, with DevOps concepts. Well-versed in orchestrating Kubernetes with Docker Compose manifests and adept at automation, scripting, containerization, and Infrastructure as Code (IaC) using Terraform, Puppet, and Ansible. Demonstrates robust scripting skills in Shell and Bash; committed to driving innovation and efficiency in DevOps practices for continuous improvement. PROFESSIONAL SUMMARY Over 8 years of Multi Cloud engineering experience, including DevOps toolchain and 1+ year as a Linux System Admin. Proficient in implementing DevOps methodologies and skilled in Cloud technologies (Azure, AWS), DevOps, Configuration management, Infrastructure automation, and CI/CD. Hands-on expertise in Containers, Application, Platform, Security, and Infrastructure across AWS, Microsoft Azure, Google Cloud GCP, and DevOps Toolchain. Integrated Docker files into CI/CD pipelines, automated building, and deployment of Docker images, and created efficient and secure Docker files. Experienced in multi-stage builds to streamline Docker image creation, using Docker Hub, Docker Engine, Docker images, Docker Weave, Docker Compose, Docker Swarm, and Docker Registry. Designed high availability and disaster recovery solutions for On Prem/Cloud landscape, Big Data architecture flows for Spark, Kafka, ElasticSearch, LogStash, and Kibana. Implemented IaaC via Terraform/Ansible, and used Azure Databricks, Snowflake, RedShift, Azure Data Factory, MuleSoft, SeeBurger, Live Stream Applications, Data Lake, Machine Learning Models across On Prem Workloads, AWS, Azure, GCP. Extensive experience in SAFe Scrum/Agile methodologies for project management operations. Experience in DWH/ETL Design Solution on AWS – Attunity, Python, Airflow, Jenkins, Teradata, ABC Framework, and Lambda functions. Expertise in AWS Code Build, Code Deploy, YAML, writing templates, testing via configuring and deploying Chef Cookbooks for Infrastructure Configuration Management. Used Security Groups, Network ACLs, Internet Gateways, NAT instances, and Route tables for securing organizations in Azure public cloud. Implemented Security, Governance, Risk, Compliance, Cost Management, and Operational Excellence with TLS, HIPAA, PCI DSS, ACL, NAT, SAML, Auth CloudStack Security Standards. Excellent communication and interpersonal skills, self-motivated, quick learner, and determination to learn new technologies, lead pre-sales efforts, and provide technical guidance for multiple delivery engagements.

Experienced Full-Stack Software Engineer with over 4 years of expertise in JavaScript, Java, Python, and Go. Proficient in cloud-based solutions (AWS, Azure), Kubernetes, Docker, and databases (RDBMS, NoSQL). Skilled in Agile practices, collaboration, and delivering robust solutions. Proven ability to design, develop, and maintain microservices-based data processing components and real-time data processing solutions. Strong experience in troubleshooting and implementing REST API Web Services. Adept at identifying and implementing short- and long- term solutions to support business needs.

Experienced IT professional with expertise in cloud migration and automation, particularly focused on Azure services. Skilled in designing, planning, and executing migrations to Azure Cloud using ARM. Proficient in Docker, Kubernetes, CI/CD pipelines, and integrating cloud services for comprehensive data processing and analytics. Strong background in AWS Redshift, Puppet, and Jenkins for system automation and continuous integration. Highly proficient in various programming languages and environment.The project involved designing and implementing a scalable and cost-effective architecture in AWS Big Data services, covering the entire data lifecycle from collection to visualization. This included creating end-to-end data pipelines using Big Data tools like Spark and Tableau for visualization, ensuring application functionality through maintenance and testing, and leveraging Spark features for efficient data preprocessing with minimal latency. Real-time solutions for Money Movement and transactional data were implemented using Kafka, Spark Streaming, and HBase, alongside a variety of other tools and languages such as Sqoop, Scala, Python, and Oozie. The work also encompassed optimizing performance, handling large datasets, and conducting code reviews and bug fixes to enhance overall system efficiency.The environment included a range of AWS services like EMR, EC2, S3, as well as various data processing tools like DynamoDB, Kafka, and Spark. Additionally, configuration management tools like BitBucket/Github and Bamboo were utilized for Continuous Integration and Continuous Deployment (CI/CD), ensuring smooth development, testing, and deployment processes. Splunk dashboards were employed for logging and monitoring, while unit test cases were written for Spark code to maintain code quality throughout the CI/CD pipeline. Overall, the project demonstrated a comprehensive understanding and utilization of Big Data technologies within an AWS environment to address complex data processing requirements.The individual possesses extensive experience in professional software engineering practices, encompassing the full software development life cycle. This includes adherence to coding standards, conducting code reviews, proficiently managing source control, and implementing robust build processes. They have demonstrated expertise in analyzing Hadoop clusters and utilizing various big data analytic tools such as Map Reduce and Hive. Notably, they have developed multiple MapReduce programs for extracting, transforming, and aggregating data from diverse file formats, including XML, JSON, CSV, and compressed files. Additionally, they have worked with Teradata parallel transport (TPT) for loading data, written Teradata Macros, and executed migration projects from Oracle/DB2 to Teradata.Furthermore, they have extensive involvement in Big Data Hadoop cluster implementation within the Business Intelligence (BI) team, focusing on data integration and large-scale system software development. Their responsibilities span from source system analysis and data modeling to ETL processes, handling both structured and unstructured data efficiently. They have a strong command of tools such as Sqoop for data import/export, Flume for data ingestion into HDFS, and the ELK stack for implementing logging frameworks on AWS. Additionally, they have developed Pig UDFs, worked on Java Rest API for CRUD operations on HBase data, and utilized Hive queries for data analysis on HBase tables. Their proficiency extends to shell scripting for scheduling data cleansing and ETL loading processes, and they actively support QA engineers in testing and troubleshooting activities.The role involved analyzing system requirements and collaborating with analysts and users. Throughout the project lifecycle, emphasis was placed on documentation, unit testing, and prioritizing development tasks. Web development primarily utilized Struts, JSP, XML, JavaScript, HTML/CSS, and AJAX. Significant contributions included designing JSP pages, developing Servlets, and integrating Spring IOC and Hibernate.Challenges were promptly addressed to enhance project outcomes, with a focus on optimizing application performance through exception handling and multi-threading. The implementation of next-generation systems leveraged technologies such as SOA, SOAP, and XSL, with SOAP protocol enabling external system interaction. Version control was managed using CVS, and project building and unit testing were facilitated by ANT scripts and JUnit.Database development involved SQL and PL/SQL, supporting various testing phases, including system, product, user acceptance, data conversion, and load testing. The technology environment encompassed Java 1.5, J2EE, RUP, Eclipse 3.1, JavaScript, JQuery, Log4J, DB2, WebSphere Server, UNIX, and IBM WebSphere Portal Server.

Dung N. Phan

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Software Engineer/ Data Analyst

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Bachelor of Science - Computer Engineering

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Software Developer

System Administrator/ Software Developer

Software Engineer/ Data Analyst

Software Engineer

Bachelor of Science - Computer Engineering

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