JORDAN NGUYEN
AWS Certified Data Architecture Specialist
linkedin.com/in/jordan-nguyen-dataengineer
github.com/JordanNguyenAWS
jordannnguyen.dev
Skills
Python, SQL, Java, JavaScript, Amazon S3, AWS Glue, Redshift, Kinesis
Certifications
AWS Certified Solutions Architect - Associate
Achieved AWS Certified Solutions Architect - Associate to validate expertise in designing and deploying scalable, secure, and highly available cloud solutions.
AWS Certified Developer - Associate
Received AWS Certified Developer - Associate to showcase proficiency in developing, deploying, and maintaining applications on the AWS platform.
Professional Summary
AWS Data Engineer with over 5 years of experience in large-scale data architecture and integration solutions. Successfully designed and implemented a real-time data pipeline for a financial services company, reducing latency by up to 40% and improving system reliability through advanced AWS Kinesis and Lambda functions. Skilled in leveraging Apache Spark and Glue ETL for complex data transformations and HiveQL for robust data querying.
Work Experience
Senior AWS Data Engineer
01/2022
Tech Company Inc
San Francisco, CA
•
Led team to design and implement a real-time data pipeline, reducing latency by 40%
•
Optimized data processing workflows, cutting costs by 30% through resource utilization improvements
•
Designed and deployed data governance framework, ensuring compliance with strict regulatory standards
•
Implemented serverless architecture for analytics, significantly reducing maintenance overhead
AWS Data Engineer
06/2020 - 12/2021
Previous Company Ltd.
San Francisco, CA
•
Developed a scalable data lake solution, handling 50TB of daily ingested data
•
Automated data backup and recovery process, reducing RTO from 4 hours to under 15 minutes
AWS Data Engineer
06/2019 - 05/2020
Data Solutions Co.
San Francisco, CA
•
Constructed data warehousing system, delivering 25% faster query response times
•
Implemented data quality checks, improving accuracy of analytics by 90%
Education
Bachelor of Science in Computer Science
09/2013 - 05/2017
San Jose State University
San Francisco, CA
Projects
Personal Data Visualization Dashboard
Developed a personal dashboard using AWS QuickSight to visualize real-time data trends from various sources, including social media and IoT devices.
github.com/JordanNguyenAWS/personal-data-dashboard
Open Source Data Analytics Library
Created an open-source library in Python for handling and analyzing large datasets, which includes functions for data cleaning, transformation, and statistical analysis.
github.com/JordanNguyenAWS/data-analytics-lib
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This resume format works well for Applicant Tracking Systems (ATS) because it clearly outlines the professional's technical skills and experience in AWS technologies relevant to a Data Engineer role. The use of specific keywords such as 'AWS Data Architecture', 'CI/CD', 'Python', and 'SQL' ensures that automated systems can easily identify the candidate's expertise when scanning through numerous applications. Additionally, including quantifiable achievements and results showcases the impact of the professional’s work in previous roles, enhancing their visibility to hiring managers who review ATS-culled resumes.
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Expert guidelines and best practices for each section of your resume.
First Name Last Name City, State, Zip Code Phone Number | Email Address LinkedIn Profile URL | Portfolio URL (Optional)
Your contact information is the first section recruiters see. Keep it concise and professional. Ensure your email address is appropriate (e.g., [email protected]). Include your LinkedIn profile for a comprehensive view of your professional journey. A portfolio or personal website is recommended for creative, technical, or design roles.
Do not include your full physical address (street number/name) for privacy reasons. Avoid including personal details like marital status, age, photo, or social security number unless specifically required in your country. Don't use unprofessional email addresses.
See clear examples of how to format contact details effectively.
John Doe 1234 Random St, Apt 56 New York, NY 10001 [email protected] github.com/aliciacode Single, 28 years old
John Doe New York, NY (555) 123-4567 | [email protected] linkedin.com/in/johndoe | github.com/johndoe | johndoe.dev
Professional Title Result-oriented [Role Name] with [Number] years of experience in [Key Skills/Industries]. Proven track record of [Major Achievement]. Skilled in [Key Technologies/Skills]. Committed to delivering [Specific Value] for [Target Industry/Company type].
A professional summary is your elevator pitch. It should be 3-5 sentences long, summarizing your experience, key skills, and major achievements. Tailor it to the job description by using relevant keywords. Focus on what makes you unique and the value you bring to potential employers.
Avoid generic objectives like 'Looking for a challenging role to grow my skills.' Recruiters want to know what value you bring to them, not what you want from them. Don't use first-person pronouns (I, me, my). Keep it concise and impactful.
Compare a weak objective with a strong professional summary.
Objective: I am a hard-working individual looking for a AWS Data Engineer position where I can learn new things and advance my career.
Senior AWS Data Engineer with 6+ years of experience in cloud-based data architecture. Reduced latency by 40% for a high-traffic platform. Expert in AWS Glue, Kinesis, and Redshift. Passionate about mentoring junior team members.
Technical Skills - Languages: [List] - Frameworks: [List] - Tools: [List] Soft Skills - [Skill 1], [Skill 2], [Skill 3]
Group your skills logically (e.g., Languages, Frameworks, Tools). Focus on hard skills relevant to the job. List skills in order of proficiency or relevance. Soft skills are better demonstrated through bullet points in your experience section rather than a bare list.
Do not list skills you are not comfortable using in an interview. Avoid using progress bars or percentages to rate your skills (e.g., "Java: 80%"). Do not include outdated technologies unless specifically required.
Practical example showing do's and don'ts for skills
AWS Lambda, Java: 95%, Python: 70%
Python, Java
Outdated tools like Oracle DB, unless specifically relevant to the job
Amazon S3, AWS Glue, Redshift, Kinesis
Job Title | Company Name | Location Month Year – Month Year - Action Verb + Context + Result (Quantified) - Led [Project] resulting in [Outcome]... - Collaborated with [Team] to implement [Feature]...
This is the core of your resume. Use reverse-chronological order (most recent first). Start each bullet with a strong action verb. Focus on achievements and impact, not just duties. Use numbers to quantify your impact (dollars, percentages, time saved, users affected). Show progression and increasing responsibility.
Avoid passive language like "Responsible for..." or "Tasked with...." Don't list every single daily task; focus on significant contributions and measurable outcomes. Avoid jargon that recruiters outside your field won't understand.
Practical example showing do's and don'ts for experiences
Responsible for developing data pipelines using AWS services.
Developed scalable data pipelines on AWS, reducing processing time by 50%.
Managed daily tasks related to database management and optimization.
Optimized database performance, cutting query times by 30% through efficient indexing strategies.
Degree Name | University Name | Location Month Year – Month Year - Relevant Coursework: [Course 1], [Course 2] - Honors/Awards: [Award Name] - GPA: X.X (if above 3.5)
List your highest degree first. If you have significant work experience, keep the education section brief. Include your GPA only if it is above 3.5 or if you are a recent graduate. Highlight relevant coursework, academic projects, honors, or leadership roles.
Do not include high school details if you have a college degree. Avoid listing every single course you took; select only the most relevant ones. Don't include graduation dates from decades ago if age discrimination is a concern in your field.
Practical example showing do's and don'ts for educations
Bachelor of Science in Computer Engineering | University of California, San Diego | San Diego, CA September 2013 – May 2017 - Courses Taken: Java Programming, Data Structures, Operating Systems, Network Security, and User Interface Design
Bachelor of Science in Computer Science | San Jose State University | San Francisco, CA September 2013 – May 2017 - Relevant Coursework: Data Structures and Algorithms, Database Systems, Cloud Computing - Honors/Awards: Dean's List (Spring '16, Fall '15) - GPA: 3.8
Project Name | Technologies Used - Briefly describe what you built and its purpose - Highlight a specific technical challenge you solved - Link to GitHub or live demo if available
Projects are excellent for demonstrating practical skills, especially if you lack work experience or are changing careers. Include a link to the GitHub repo or live demo if possible. Focus on projects that show problem-solving skills and relevant technologies for the target role.
Don't include trivial tutorials unless you significantly expanded on them. Avoid projects that are outdated, incomplete, or irrelevant to the role you're applying for. Don't just list technologies—explain what you built and why it matters.
Practical example showing do's and don'ts for projects
Built a basic CRUD application using AWS Lambda and DynamoDB, following an online tutorial. The project is incomplete with missing documentation and no live demo available.
Developed a real-time analytics dashboard using AWS Kinesis and QuickSight to monitor IoT device performance in real-time. Utilized serverless architecture to ensure scalability without manual intervention. Link: GitHub Repo
Common questions about this role and how to best present it on your resume.
Essential skills include knowledge of AWS services such as S3, RDS, and Redshift, proficiency in SQL and data modeling, and experience with ETL processes.
Highlight transferable skills and experiences relevant to the position. Emphasize your ability to quickly adapt and contribute effectively despite having more extensive experience than required.
Yes, including projects that demonstrate your technical abilities with AWS services can strengthen your application and show hands-on experience beyond formal job roles.
Consider obtaining the AWS Certified Data Analytics Specialty or AWS Certified Developer - Associate to validate your expertise in cloud data solutions.
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