🎯 Choose Role - Pick Your Data Specialty

Select a specific data engineering role and get your detailed learning path.

Usage

/choose-role [role-name]
# or
/choose-role
# for interactive selection

Available Roles

data-engineer - Master pipelines, ETL, big data (PRIMARY)
backend-engineer - APIs, databases, data services
data-scientist - ML, statistics, insights
ml-engineer - Deep learning, LLMs, AI
cloud-engineer - Cloud architecture, data warehousing
devops-engineer - Infrastructure, CI/CD, reliability

Examples

/choose-role data-engineer
/choose-role ml-engineer
/choose-role cloud-engineer

What You Get

✅ Comprehensive agent overview (2,000+ words) ✅ 7-phase learning path with weekly breakdown
✅ Core technologies and tools (30+ technologies) ✅ Career progression with salary ranges ✅ Real-world specializations ✅ Success checklists with milestones ✅ Next steps and resource recommendations

Role Deep Dives

Data Engineer - PRIMARY ROLE

40-week mastery path:

Week 1-4: Python & SQL foundations
Week 5-10: SQL mastery & databases
Week 11-16: ETL pipelines & Airflow
Week 17-22: Big Data (Spark, Hadoop)
Week 23-28: Data warehousing (Snowflake, BigQuery)
Week 29-34: Modern tools (Kafka, dbt, Data Mesh)
Week 35-40: Production systems & leadership

Market: ⭐⭐⭐⭐⭐ Highest demand
Salary: $80K-$300K+ range
Best For: System builders, scalability enthusiasts

Backend Engineer

36-week learning path focused on data APIs:

Week 1-4: Foundations & networking
Week 5-12: Language mastery (Python/Node/Java)
Week 13-18: SQL & NoSQL databases
Week 19-24: API development (REST, GraphQL)
Week 25-28: Security & authentication
Week 29-36: Microservices, async, deployment

Market: ⭐⭐⭐⭐ Very hot
Salary: $70K-$250K+ range
Best For: API builders, service-oriented

Data Scientist

40-week ML & analytics path:

Week 1-6: Python fundamentals
Week 7-12: Pandas, NumPy, SQL
Week 13-16: Exploratory data analysis
Week 17-22: Statistics & mathematics
Week 23-30: ML algorithms
Week 31-34: Feature engineering
Week 35-40: Advanced ML & specialization

Market: ⭐⭐⭐⭐⭐ Extremely hot
Salary: $80K-$300K+ range
Best For: Data lovers, math enthusiasts

ML & AI Engineer

40-week cutting-edge AI path:

Week 1-8: Deep learning foundations
Week 9-14: PyTorch & TensorFlow
Week 15-22: Advanced architectures
Week 23-30: LLMs & generative AI
Week 31-34: Multimodal AI
Week 35-38: AI agents & systems
Week 39-40: Production ML

Market: ⭐⭐⭐⭐⭐ Hottest in industry
Salary: $100K-$400K+ range
Best For: AI enthusiasts, researchers

Cloud Data Engineer

36-week cloud architecture path:

Week 1-4: Cloud fundamentals
Week 5-14: Primary cloud (AWS/GCP/Azure)
Week 15-22: Data platforms (warehouses, lakes)
Week 23-28: Infrastructure as Code
Week 29-32: Security & compliance
Week 33-36: Monitoring & optimization

Market: ⭐⭐⭐⭐⭐ Extremely hot
Salary: $85K-$300K+ range
Best For: Architects, scale thinkers

DevOps Engineer

40-week infrastructure path:

Week 1-4: Linux & systems
Week 5-8: Bash scripting
Week 9-10: Git & version control
Week 11-16: Docker & containers
Week 17-24: Kubernetes
Week 25-30: Cloud platforms
Week 31-34: Infrastructure as Code
Week 35-38: CI/CD
Week 39-40: Monitoring & observability

Market: ⭐⭐⭐⭐⭐ Premium demand
Salary: $75K-$280K+ range
Best For: Automation lovers, reliability engineers

🎯 How to Choose

Build your own learning system? → Data Engineer
Create APIs & services? → Backend Engineer
Extract insights from data? → Data Scientist
Work on cutting-edge AI? → ML & AI Engineer
Design cloud architecture? → Cloud Engineer
Automate & keep systems running? → DevOps Engineer

🚀 After Choosing

Read the agent overview (2,000+ words per role)
Start week 1 of your phase
Use /skill-deep-dive for specific technologies
Use /project-ideas for hands-on learning
Use /roadmap-status to track progress
Use /interview-prep when job ready

Next: Run /skill-deep-dive [skill] to master specific technologies!