diff --git a/app/blog/exploring-the-intersection-of-design-ai-and-design-engineering/page.mdx b/app/blog/exploring-the-intersection-of-design-ai-and-design-engineering/page.mdx deleted file mode 100644 index b9fcf2f..0000000 --- a/app/blog/exploring-the-intersection-of-design-ai-and-design-engineering/page.mdx +++ /dev/null @@ -1,101 +0,0 @@ - - -# Exploring the Intersection of Design, AI, and Design Engineering - -Design and artificial intelligence (AI) are increasingly intertwined, driving innovation across industries. As technology evolves, the role of design engineering is more critical than ever, bridging creativity and functionality. - ---- - -## The Evolving Role of AI in Design - -AI is no longer just a backend tool—it’s becoming an active collaborator in the creative process. From generating design ideas to optimizing layouts, AI offers endless possibilities. For instance: - -- **Generative Design**: AI algorithms can generate thousands of design variations based on constraints, helping designers explore ideas faster. -- **User Experience Optimization**: AI analyzes user behavior to suggest improvements, enabling data-driven design decisions. -- **Automation**: Repetitive tasks like resizing assets or formatting layouts can be automated, freeing up designers for more strategic work. - -## Challenges and Opportunities - -While AI empowers designers, it also raises challenges: - -### Challenges - -- **Ethical Design**: AI systems may unintentionally reinforce biases. Designers must ensure inclusivity and fairness. -- **Loss of Control**: Relying too heavily on AI can dilute the human touch in design. -- **Learning Curve**: Integrating AI tools requires new skills, which can be daunting for some designers. - -### Opportunities - -- **Enhanced Creativity**: AI can inspire by offering unconventional ideas. -- **Efficiency Gains**: Automation allows for rapid iteration and prototyping. -- **Scalability**: AI enables personalized experiences at scale, a growing demand in today’s market. - ---- - -## Design Engineering: The Glue Between Creativity and Execution - -Design engineering ensures that the gap between creative vision and technical execution is seamless. It combines the artistry of design with the precision of engineering. - -### Key Principles of Design Engineering - -1. **Systems Thinking**: Viewing a design holistically ensures all components work together cohesively. -2. **Collaboration**: Effective communication between designers and developers is crucial for successful outcomes. -3. **Iterative Process**: Building, testing, and refining are fundamental to achieving the best results. - -> "Good design is as little design as possible." — Dieter Rams - -### Tools of the Trade - -Modern design engineers leverage tools like: - -- **Figma** and **Sketch** for prototyping -- **Motion** for creating smooth animations -- **Tailwind CSS** for streamlined styling -- **Git** for version control and collaboration - ---- - -## AI and Design Engineering: A Symbiotic Relationship - -The integration of AI into design engineering creates powerful synergies: - -- **Prototyping with AI**: AI-driven tools like ChatGPT assist in generating content for prototypes, accelerating the design process. -- **Predictive Analytics**: Engineers use AI to predict performance issues and optimize designs in real-time. -- **Accessibility Improvements**: AI tools automatically detect and fix accessibility concerns, ensuring compliance. - -### Case Study: Motion-Primitives - -Motion-Primitives demonstrates how AI and design engineering come together. By leveraging Framer Motion and Tailwind CSS, it simplifies the creation of dynamic, responsive interfaces. AI can enhance this by: - -- Generating motion patterns based on user preferences. -- Optimizing performance for different devices. -- Automating testing for cross-browser compatibility. - ---- - -## Conclusion - -The intersection of AI, design, and design engineering is reshaping the industry. By embracing AI while staying grounded in design principles, professionals can push boundaries and create experiences that are both innovative and human-centered. The future lies in collaboration—not only between humans and machines but also among designers, engineers, and AI. - ---- - -### Questions for Reflection - -- How can we ensure AI remains a tool for empowerment rather than replacement? -- What steps can design engineers take to integrate AI responsibly into their workflows? - -### Further Reading - -- [Designing for AI](https://example.com/designing-for-ai) -- [The Future of Design Systems](https://example.com/future-design-systems) -- [Ethical AI Guidelines](https://example.com/ethical-ai) - ---- - -### Music for Inspiration - -Listening to music while working? Check out _"Motion"_ by Tycho—a perfect blend of creativity and rhythm. diff --git a/app/blog/faang-interview-guide/page.mdx b/app/blog/faang-interview-guide/page.mdx new file mode 100644 index 0000000..07d062c --- /dev/null +++ b/app/blog/faang-interview-guide/page.mdx @@ -0,0 +1,137 @@ + + +# FAANG Data Engineering Interview Guide + +A comprehensive guide to help you prepare for data engineering interviews at top tech companies like Facebook, Amazon, Apple, Netflix, and Google. + +--- + +## Introduction + +Set the stage: +- What is this guide about? +- Why are FAANG interviews unique? +- Who is this guide for? + +--- + +## Interview Process Overview + +Summarize the general interview flow across FAANG companies: +- Application and recruiter screen +- Technical phone screens +- Take-home assignments (if applicable) +- On-site/virtual onsite interviews +- Final rounds and offer stage + +--- + +## Core Skills to Master + +List the essential areas you’ll be tested on: + +### 1. SQL & Data Manipulation +- Complex joins, aggregations, window functions +- Common questions and practice tips + +### 2. Data Modeling +- Star vs. snowflake schema +- Normalization vs. denormalization +- Designing scalable data warehouses + +### 3. ETL and Pipelines +- Building resilient pipelines +- Workflow orchestration tools (Airflow, AWS Step Functions) +- Real-time vs batch processing + +### 4. Big Data Ecosystem +- Hadoop, Spark, Hive, Presto +- Hands-on experience and where to practice + +### 5. Python or Scala for Data Engineering +- Writing clean, testable data pipelines +- Pandas vs PySpark – when to use what +- Basic coding problems and data structures + +### 6. System Design for Data Engineers +- Designing a logging pipeline, recommendation system, etc. +- Trade-offs: latency, throughput, fault tolerance +- Data lake vs. data warehouse + +### 7. Behavioral Interviews +- STAR format +- Leadership principles (especially for Amazon) +- Cross-functional collaboration examples + +--- + +## Company-Specific Tips + +### Amazon +- Focus on SQL, behavioral alignment with leadership principles +- Redshift, Glue, Lambda knowledge is helpful + +### Google +- More emphasis on algorithms and coding +- BigQuery, Dataflow, and systems thinking + +### Facebook (Meta) +- Expect deep SQL, data pipeline design, and product sense +- Communication and collaboration are key + +### Apple +- Focus on clean, maintainable code and end-to-end pipeline knowledge +- Emphasis on craftsmanship and reliability + +### Netflix +- Strong emphasis on data architecture and ownership +- Python, Spark, and business alignment are valued + +--- + +## Study Resources + +A few resources you can recommend or personally found helpful: + +- [LeetCode – SQL & Easy Python Problems](https://leetcode.com) +- [Interview Query](https://interviewquery.com) +- [Designing Data-Intensive Applications by Martin Kleppmann] +- [Data Engineering Zoomcamp](https://github.com/DataTalksClub/data-engineering-zoomcamp) +- [Apache Spark and the Unified Analytics Engine (Databricks)] + +--- + +## Practice Questions + +Add a few sample questions or link to a list: + +- Write a SQL query to find the second highest salary. +- Design a data pipeline that ingests streaming data and aggregates metrics every 10 minutes. +- What’s the difference between row-based and columnar storage? + +--- + +## Final Tips + +Wrap-up advice for candidates: + +- Practice explaining your projects clearly +- Mock interviews with peers or platforms like Pramp +- Document and reflect after every interview + +--- + +## Good Luck! + +You’ve got this! Preparation, consistency, and clarity go a long way in landing your dream data engineering job at FAANG. + +--- + +## Stay Connected + +Feel free to reach out for questions, mock interviews, or collaboration! +[LinkedIn](#) • [Email](#) • [GitHub](#) diff --git a/app/blog/my-journey-at-amazon/page.mdx b/app/blog/my-journey-at-amazon/page.mdx new file mode 100644 index 0000000..3e1e93d --- /dev/null +++ b/app/blog/my-journey-at-amazon/page.mdx @@ -0,0 +1,72 @@ + + +# My Experience Working in Data at Amazon + +## Introduction + +A brief overview of my role at Amazon and what this post will cover. +(Example: what team you were on, the kind of work you did, and your general goals in writing this.) + +--- + +## Getting Started at Amazon + +Talk about how you joined, what onboarding was like, and your first impressions. +- Team structure +- Initial projects +- Culture and expectations + +--- + +## The Day-to-Day Work + +Describe what a typical day looked like. +- Tools and tech stack +- Meetings and collaboration +- Challenges and rewards + +--- + +## Key Projects and Impact + +Highlight some important projects you worked on. +- Problem statements +- Technologies used +- Outcomes and business impact + +--- + +## What I Learned + +Reflect on the technical and non-technical lessons. +- Skills gained (e.g., SQL optimization, data pipeline design) +- Working with cross-functional teams +- Communication and decision-making at scale + +--- + +## The Amazon Culture + +Share your take on the work environment and company values. +- Leadership Principles in action +- Internal mobility +- Performance reviews and feedback + +--- + +## Advice for Others Interested in Data Roles at Amazon + +Tips for aspiring Amazonians or those interested in data roles at big tech companies. +- Interview prep +- Skill-building recommendations +- What to expect + +--- + +## Conclusion + +A wrap-up of your time at Amazon and what you’re doing now (or diff --git a/app/data.ts b/app/data.ts index 479cad3..ebbb87a 100644 --- a/app/data.ts +++ b/app/data.ts @@ -2,7 +2,8 @@ type Project = { name: string description: string link: string - video: string + // video: string + image: string id: string } @@ -27,93 +28,115 @@ type SocialLink = { link: string } +// export const PROJECTS: Project[] = [ +// { +// name: 'Token Traveler', +// description: 'Augmented Reality Android mobile app where players collect beer, park, and coffee tokens.', +// link: 'https://github.com/odowdbrendan/TokenTraveler', +// video: +// 'https://github.com/odowdbrendan/TokenTraveler', +// id: 'project1', +// }, +// { +// name: 'Fantasy Football Helper', +// description: +// 'Data-driven fantasy football companion that uses predictive analytics and AI to guide your team management decisions.', +// link: 'https://www.google.com', +// video: +// 'https://github.com/odowdbrendan/', +// id: 'project2', +// }, +// ] + export const PROJECTS: Project[] = [ { - name: 'Motion Primitives Pro', - description: - 'Advanced components and templates to craft beautiful websites.', - link: 'https://pro.motion-primitives.com/', - video: - 'https://res.cloudinary.com/read-cv/video/upload/t_v_b/v1/1/profileItems/W2azTw5BVbMXfj7F53G92hMVIn32/newProfileItem/d898be8a-7037-4c71-af0c-8997239b050d.mp4?_a=DATAdtAAZAA0', + name: 'Token Traveler', + description: 'Augmented Reality Android mobile app where players collect beer, park, and coffee tokens.', + link: 'https://github.com/odowdbrendan/TokenTraveler', + image:'/avl.jpg', id: 'project1', }, { - name: 'Motion Primitives', - description: 'UI kit to make beautiful, animated interfaces.', - link: 'https://motion-primitives.com/', - video: - 'https://res.cloudinary.com/read-cv/video/upload/t_v_b/v1/1/profileItems/W2azTw5BVbMXfj7F53G92hMVIn32/XSfIvT7BUWbPRXhrbLed/ee6871c9-8400-49d2-8be9-e32675eabf7e.mp4?_a=DATAdtAAZAA0', + name: 'Fantasy Football Helper', + description: + 'Data-driven fantasy football companion that uses predictive analytics and AI to guide your team management decisions.', + link: 'https://www.google.com', + image:'/avl.jpg', id: 'project2', }, ] export const WORK_EXPERIENCE: WorkExperience[] = [ { - company: 'Reglazed Studio', - title: 'CEO', - start: '2024', + company: 'Amazon', + title: 'Data Engineer', + start: '2023', end: 'Present', - link: 'https://ibelick.com', + link: 'https://health.amazon.com/onemedical', id: 'work1', }, { - company: 'Freelance', - title: 'Design Engineer', - start: '2022', - end: '2024', + company: 'PwC', + title: 'Data Engineer', + start: '2023', + end: '2023', link: 'https://ibelick.com', id: 'work2', }, { - company: 'Freelance', - title: 'Front-end Developer', - start: '2017', - end: 'Present', - link: 'https://ibelick.com', + company: 'Amazon', + title: 'Business Intelligence Engineer', + start: '2021', + end: '2023', + link: 'https://pharmacy.amazon.com/', id: 'work3', }, + { + company: 'Farragut Systems', + title: 'SQL Developer', + start: '2021', + end: '2021', + link: 'https://farragut.com/', + id: 'work4', + }, + { + company: 'HomeTrust Bank', + title: 'Business Intelligence Developer', + start: '2019', + end: '2021', + link: 'https://htb.com/', + id: 'work4', + }, ] export const BLOG_POSTS: BlogPost[] = [ { - title: 'Exploring the Intersection of Design, AI, and Design Engineering', - description: 'How AI is changing the way we design', - link: '/blog/exploring-the-intersection-of-design-ai-and-design-engineering', + title: 'My Journey Working at Amazon', + description: 'My experience working in data roles at Amazon.', + link: '/blog/my-journey-at-amazon', uid: 'blog-1', }, { - title: 'Why I left my job to start my own company', - description: - 'A deep dive into my decision to leave my job and start my own company', - link: '/blog/exploring-the-intersection-of-design-ai-and-design-engineering', - uid: 'blog-2', - }, - { - title: 'What I learned from my first year of freelancing', - description: - 'A look back at my first year of freelancing and what I learned', - link: '/blog/exploring-the-intersection-of-design-ai-and-design-engineering', - uid: 'blog-3', + title: 'FAANG Data Engineering Interview Guide', + description: 'Get help passing FAANG data interviews', + link: '/blog/faang-interview-guide', + uid: 'blog-1', }, ] export const SOCIAL_LINKS: SocialLink[] = [ { label: 'Github', - link: 'https://github.com/ibelick', + link: 'https://github.com/odowdbrendan', }, { - label: 'Twitter', - link: 'https://twitter.com/ibelick', + label: 'X', + link: 'https://x.com/brendanodowd16', }, { label: 'LinkedIn', - link: 'https://www.linkedin.com/in/ibelick', - }, - { - label: 'Instagram', - link: 'https://www.instagram.com/ibelick', + link: 'https://www.linkedin.com/in/brendanodowd/', }, ] -export const EMAIL = 'your@email.com' +export const EMAIL = 'brendan.pp.odowd@gmail.com' diff --git a/app/footer.tsx b/app/footer.tsx index 0806a9a..431cb77 100644 --- a/app/footer.tsx +++ b/app/footer.tsx @@ -70,10 +70,10 @@ export function Footer() { return (