You know that moment at a tech conference when someone casually asks, “Have you considered applying for GDE?” and you think they’re joking?

I was at DevFest Bangalore in late 2024, eating samosas between talks on Vertex AI and FlutterFlow. A conversation about GCP pipelines turned into “Wait, you already do this stuff - why aren’t you a GDE?”

I hadn’t considered it. I was just… doing the work. Blogging about data pipelines. Contributing PRs to Spark-XML and llm4s. Mentoring engineers on Scala and GCP. Running workshops. Building tools.

Turns out that’s exactly what the Google Developer Expert (GDE) program looks for.

I applied. No flashy cover letter. No polished video. Just documentation of what I’d been doing for 12+ years. Three months later: accepted.

This is the complete breakdown - from contribution tracking to interview questions to what actually matters.

Why this matters

Here’s the GDE reality nobody tells you:

What people think GDE is:

• You need to be famous
• You must speak at 20 conferences
• You need viral blog posts
• You’re competing against influencers

What GDE actually is:

• Recognition for consistent contribution
• Community impact over personal brand
• Depth in specific domains
• Teaching and enabling others

The cost of not applying:

• Your contributions go unrecognized
• You miss networking opportunities
• You keep thinking “maybe someday”
• You undervalue your own impact

What I needed:

• A system to track contributions
• Proof of community impact
• Domain expertise demonstration
• Clear communication style

This post shows you what actually worked.

Part 1 - Why I chose the GDE path

For me, GDE wasn’t about a title - it was about recognizing and amplifying the work I was already doing. I’ve been in the engineering game for 12+ years - data pipelines, architecture, tooling, open source, mentoring - and the GDE program felt like a natural next step to formalize those contributions.

My core focus areas were:

• AI/ML
• Google Cloud Platform (GCP)
• Dart

These weren’t chosen just because they’re trendy - but because they aligned with what I use, teach, and care about deeply.

Part 2 - The backstory: from DevFest to decision

In late 2024, I attended DevFest Bangalore - just another tech weekend, or so I thought. Between talks on Vertex AI, FlutterFlow, Web, and GCP use cases, I realized something weird: most of the topics mirrored what I’d already been working on.

I had been building CI/CD for data pipelines, working with GCP (DataProc, BigQuery, Storage, Pub/Sub), implementing real-world AI/ML use cases, and mentoring folks through functional programming, Scala, Dart, and data platforms.

One conversation turned into another (yes, samosas were involved), and someone suggested I apply for the Google Developer Expert program. I hadn’t thought about it before - but the more I looked into it, the more I realized this program wasn’t about being a know-it-all; it was about being useful to other devs.

So I applied. No flashy cover letter. No polished video. Just a submission of what I’d already been doing for years. And it worked.

Part 3 - My foundation: what I had to show

Before applying, I took a long look at what I had already built. GDE is not something you prep for like an exam. It’s something you grow into by doing real work that helps others.

Here’s what made up my contribution pillars:

Blogging and technical writing

• vitthalmirji.com : I moved away from WordPress to a custom Hugo + Nginx setup to better reflect my engineering style. All content is markdown-based and versioned.
• Tutorials, guides, and writeups on data contracts, pipeline architectures, functional data engineering, and more.

Talks, CFPs, and community work

• Scala Days 2025 Talk Proposal: I submitted a talk centered around my real-world experience building scalable data tools using Scala and functional design - see Scala CFP Submission .
• Regular contributor and volunteer for Java, Scala, and Google Developer communities in Mumbai, Pune, and Belgaum.
• Led and mentored multiple classroom and workshop-based sessions on data engineering and tooling.

Open source contributions

• llm4s PR #101: Improved SDK usability and onboarding via Giter8 template – link to PR .
• Databricks Spark-XML: Contributed feature for exploding deeply nested XML into flat, readable DataFrames.
• Apache Spark + HBase Connector (SHC): Added enhancements for Google BigTable support.
• My own tools on GitHub :
  • datapipelines-essentials-python
  • dataengineering-savvy
  • Accelerators for Spark, HBase, Bash-based pipelines

Teaching and mentorship

• Ran workshops and mentored engineers on Data Engineering, GCP, and tooling best practices.
• Created and delivered a beginner-level training curriculum on Product Architecture for Manufacturing Engineers.

Part 4 - The application process: what it’s really like

The GDE process is rigorous but human. Here’s the gist:

• Step 1: Track your contributions – Blog posts, OSS PRs, mentoring sessions, community events. I used a spreadsheet to log these like a nerdy historian with version control.
• Step 2: Get a referral – - This came through someone who was familiar with my community work and OSS visibility.
• Step 3: Interview(s) – These focused on:
  • Depth in my declared domains (AI/ML, GCP, Dart)
  • Impact on the community
  • Originality and clarity in communication

Spoiler: It’s not about being the smartest person in the room. It’s about clarity, consistency, and care for the community.

Part 5 - What I learned along the way

Here are the things I wish someone had told me earlier:

• Start tracking now: Contributions get lost in the noise if you don’t document them.
• Pick quality over quantity: One solid article or OSS feature > 10 shallow tutorials.
• Mentorship = leverage: Getting feedback from existing GDEs was a game-changer.
• Your voice matters: Write in your own style. Don’t sound like a technical brochure.
• You don’t apply for GDE - you grow into it: If you’re already contributing, the application is just the paperwork.

Part 6 - What’s next

The GDE journey isn’t a destination - it’s an amplifier.

• I’m continuing work on:
  • Archetype: A code-generation framework for standardized data pipelines
  • DQ Framework: For automated data quality testing and tracking
  • Utilities APIs: Dev-ready libraries for Gated CRQ and CI/CD tooling
• I plan to contribute deeper to Scala’s ecosystem, and I’m actively exploring mentorship and collaboration opportunities in the functional programming and GCP spaces.

Part 7 - Final thoughts

If you’re on the fence about GDE, here’s my advice:

• Don’t chase the badge - chase impact.
• Show up consistently. Write. Build. Speak. Teach.
• Find your niche and build tools, not just tutorials.
• And when you’re ready… go for it.

Want to talk more about the GDE process or need help with your application? DM me on Twitter or email me .

If you’re attending community events, mentoring others, or just building cool stuff and sharing it - you might already be walking the road. Just document it, reflect on it, and apply when it feels natural. That’s all I did.

TL;DR

• The trigger: DevFest Bangalore 2024 - someone asked “Why aren’t you a GDE?” over samosas during tech talks
• The realization: I was already doing the work - blogging, OSS contributions, mentoring, workshops - just hadn’t documented it
• What GDE actually is: Recognition for consistent community contribution, not a popularity contest or fame requirement
• Common myths debunked: Don’t need to be famous, don’t need 20 conference talks, don’t need viral posts, not competing against influencers
• What matters: Consistent contribution, community impact over personal brand, depth in specific domains, teaching and enabling others
• My focus areas: AI/ML, GCP, Dart - chosen because I use, teach, and care about them (not trendy)
• 12+ years background: Data pipelines, architecture, tooling, open source, mentoring across engineering domains
• Blog foundation: vitthalmirji.com moved from WordPress to Hugo + Nginx, markdown-based content, version-controlled
• Key OSS contributions: llm4s PR #101 (Giter8 template), Databricks Spark-XML (nested XML flattening), Apache Spark HBase Connector (BigTable support)
• My GitHub projects: datapipelines-essentials-python, dataengineering-savvy, Spark/HBase/Bash accelerators
• Community work: Scala Days 2025 CFP submission, volunteer for Java/Scala/Google communities (Mumbai, Pune, Belgaum), classroom workshops
• Mentorship: Data Engineering training, GCP best practices, Product Architecture curriculum for Manufacturing Engineers
• Application process: Step 1 = track contributions (used spreadsheet like nerdy historian), Step 2 = get referral (community work), Step 3 = interviews
• Interview focus: Depth in declared domains (AI/ML, GCP, Dart), impact on community, originality and clarity in communication
• Not about being smartest: It’s about clarity, consistency, and care for the community
• Key lessons: Start tracking now, quality > quantity (1 solid article > 10 shallow tutorials), mentorship = leverage, write in your own voice
• The truth: You don’t apply for GDE - you grow into it (application is just paperwork for work you’re already doing)
• What’s next: Archetype (code-gen for data pipelines), DQ Framework (automated quality testing), Utilities APIs (Gated CRQ + CI/CD)
• Final advice: Don’t chase the badge - chase impact, show up consistently (write, build, speak, teach), find your niche and build tools
• Bottom line: If you’re contributing to communities, mentoring, building and sharing - you might already be on the road, just document it
• Three-month timeline: Applied with no flashy cover letter or video, just documentation of 12+ years of work → accepted

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Your voice matters. Let the world hear it.