Skills Pattern Analysis (SPA): How to Reverse-Engineer Your Dream Tech Role

What if you could reverse-engineer your dream roles to figure out exactly which skills to develop? Skills Pattern Analysis (SPA) is a systematic approach to career planning that helps you identify patterns in job requirements and strategically direct your career growth.

The Method: How It Works

Whenever you find a position you like (location/company/role/perks), do this:

1. Check the minimal requirements listed in the job posting
2. Copy the position title (example: "Software Engineer - Backend at Google") and the relevant part of the job description into a document
3. Repeat this process for all positions you like, would like to have, or are interested in
4. After collecting several roles, analyze which "required skills" overlap and appear frequently
5. Use these insights to direct your career: Go in the direction that will help you acquire these recurring skills

How I Used This Method (Real Example)

When I first implemented this framework, I was targeting roles I liked in big tech companies in Zurich and across Europe. Here's what I discovered:

Skills That Kept Appearing

After analyzing multiple job postings, clear patterns emerged:

• Language-wise: Java appeared frequently and applied to many (if not all) of my target roles
• Technical skills: Large-Scale Distributed Systems were often required
• Secondary skills: Full-Stack/Frontend skills and Python appeared sometimes, but not as consistently

The Strategic Decision

This analysis helped me narrow down my target roles: most of them involved backend distributed systems and Java. I made strategic decisions based on this:

What I Prioritized:

• For my MSc thesis, I worked on software instrumentation and performance analysis of Java distributed systems
• During my MSc, I chose courses that would help me upskill in this area
• I didn't shy away from full-stack work (like my Amazon internship) since FE skills appeared occasionally

What I Deprioritized:

• ML/AI wasn't frequently recurring in these roles, so while useful, I didn't prioritize it heavily
• I stayed away from tangents that were good on paper but inefficient for my goals: security, robotics, GraphQL, VR/CV, etc.

Creating Your Target Roles List

I recommend everyone create a curated list of target roles and companies. Here's how to make it effective:

Keep It Curated

Your list should only include roles you genuinely like and that are good for you. Cut out the junk. Quality over quantity is essential here.

Keep It Actionable

Avoid creating a "Frankenstein list" with random good-sounding jobs (mixing London HFT roles, big tech positions, academia, management, engineering, etc.).

The goal: Implement a targeted search and prepare to "attack" this carefully-crafted set of roles with your best abilities and beat the competition.

Two Different Documents You Need

It's important to maintain two separate documents:

1. The Target Roles List

• A simple list of roles and companies
• Can be an Excel sheet, Google Doc, etc.
• Just names and basic information

2. The Skills Analysis Document

• Contains detailed text for each position
• Copy at least all the "minimal requirements" from job postings
• Potentially include information about what the job entails, what the team does, etc.
• This is your pattern analysis goldmine

Case Study: VR/CV vs. Backend Systems

Here's a real decision I had to make: Many big tech roles in Zurich required Virtual Reality and Computer Vision skills. Should I pivot to VR/CV to access these high-paying roles?

My Analysis

I had the background to make this transition (BSc in Robotics, signal processing, mathematical modeling, ML experience), but I decided to stay in backend/distributed systems. Here's my reasoning:

1. Amount of Opportunities

• Backend & infrastructure roles ≈ CV/VR roles in big tech Zurich
• Similar pool size for both paths

2. Competition Analysis

• CV/VR had less competition BUT higher caliber (world-class PhDs from ETH and EPFL)
• Backend/distributed systems had more competition BUT more approachable (regular CS graduates from various European universities)

3. Geographic Flexibility

• I was open to other European locations and potentially the US
• CV/VR is a narrow niche—if I didn't get a big tech Zurich role, alternatives would be low-paying startups
• Backend/distributed systems offered more options: Swiss tech companies (UBS, GetYourGuide), big tech roles across Europe, strong demand in the US

4. Long-Term Versatility

• Backend skills would be useful if I later wanted to build SaaS products
• CV/VR skills could limit me to that specific field
• Backend expertise applies broadly across the industry

5. Personal Enjoyment

• Backend/distributed systems felt more fun to work on

Advanced Technique: Don't Stop at Open Positions

Open positions are a starting point, but you can go deeper:

Research Company Teams

Look at the "people" section of your target companies on LinkedIn:

• How many employees work there?
• What do they actually do?
• What's the size of different teams?

Example insight: Meta having 30 CV roles isn't the same as Google having 2-3k backend roles. This context matters for your decision-making.

Analyze Senior Roles

Create a document tracking skills required for very senior positions at your target companies. This helps with:

• Mid to long-term career planning
• Understanding which skills have the most growth potential
• Seeing if your current path aligns with senior-level opportunities

My Results Using This Framework

I joined Oracle Zurich working on MySQL Cloud's backend (Control Plane team) with $200k+ total compensation, working on—surprise—distributed systems in Java.

The interesting part: I didn't initially target Oracle because they didn't list many positions publicly. Most of their pipeline was through internal referrals. But because I had focused on backend/distributed systems/cloud, someone in my network knew I was the right fit and offered me an interview.

Long-Term Outcomes of This Approach

Following this strategic framework led to multiple benefits:

✅ Gained experience in a popular tech vertical (backend/distributed systems/cloud)

✅ Landed a job among target roles (big tech Zurich) that aligned with my financial goals

✅ Chose something versatile that's useful for building SaaS products later

✅ Selected a broad specialty that's valuable for remote roles, not just Zurich positions

✅ Positioned myself well for climbing the big tech ladder with expertise valued by multiple companies

How to Implement This Framework

Step 1: Collect Data (1-2 months)

• Identify 15-30 roles you genuinely want
• Copy full job descriptions, especially requirements
• Include variety but stay within your general career direction

Step 2: Analyze Patterns (1 week)

• Identify skills that appear in 50%+ of roles (high priority)
• Note skills that appear in 20-40% of roles (medium priority)
• Mark skills appearing rarely (low priority unless personally important)

Step 3: Make Strategic Decisions (ongoing)

• Prioritize high-frequency skills in your current role
• Choose projects that develop these skills
• Take courses or certifications in key areas
• Network with people who have these skills

Step 4: Review and Adjust (quarterly)

• Update your target roles list as your interests evolve
• Add new positions as you discover them
• Reassess skill patterns every 3-6 months
• Adjust your development focus accordingly

Key Takeaways

• Be systematic: Don't just apply randomly—understand what your dream roles require
• Look for patterns: Skills that appear repeatedly across roles are your North Star
• Think long-term: Consider geographic flexibility, market demand, and personal growth
• Analyze competition: It's not just about what's in demand, but where you can realistically compete
• Stay flexible: Your analysis document should evolve as you grow and the market changes
• Network strategically: Focus on communities and connections in your target skill areas

This framework transforms vague career aspirations into concrete skill development goals. It's not about chasing trends—it's about making informed decisions based on data from roles you actually want.

Conclusion

Skills Pattern Analysis is one of the most practical tools you can use to strategize and thrive in your tech career in Europe. Instead of randomly upskilling or following the latest hype, you're making deliberate choices based on real market data from roles you genuinely want.

The best part? This method works whether you're a junior developer planning your first few years or a senior engineer plotting your next career move. Start collecting those job descriptions today, and let the patterns guide your growth.