Transforming raw data into meaningful insights, one pipeline at a time
class DataEngineer:
def __init__(self):
self.name = "Prakash Chebolu"
self.role = "Data Engineer"
self.passions = ["Data Architecture", "Cloud Computing", "ETL Pipelines", "Good Food"]
self.current_focus = "Building scalable data solutions on AWS"
def daily_routine(self):
return [
"☕ Coffee first",
"🔧 Design data pipelines",
"☁️ Deploy on AWS",
"📊 Monitor & optimize",
"🍕 Think about food"
]
- 🔧 Building: Scalable ETL pipelines on AWS
- 📚 Learning: Advanced Spark optimization techniques
- 🌱 Growing: Cloud-native data architecture skills
- 🤝 Collaborating: On open-source data tools
- 🍜 I can debug data pipelines and recommend great restaurants with equal enthusiasm
- ☁️ I dream in SQL and wake up thinking about cloud costs
- 📈 My code is like a good recipe - it gets better with each iteration
- 🎮 When not engineering data, I'm probably planning my next meal
Whether you want to discuss the latest in data engineering, share a cool AWS trick, or recommend a great place to eat - I'm always up for a good conversation!
"Data is the new oil, but only if you know how to refine it" ⚡