D:

Full-Stack Software Engineering services

- Lead the design, development, enhancement, and maintenance of software applications leveraging Python programming and modern cloud platforms
- Drive frontend, backend, and API development, with a focus on Python-based services and cloud-native architectures
- Enable seamless integration with internal systems, platforms, and data sources, including cloud-based services such as storage, compute, and data pipelines
- Build and deliver scalable, high-performance solutions using contemporary frameworks and cloud technologies (GCP/AWS/Azure/SF)
- Ensure high code quality through rigorous testing, debugging, and defect resolution across all application layers, including cloud deployments
- Contribute to and uphold engineering excellence by actively participating in code reviews and enforcing best practices in programming and cloud engineering
- Support deployment, CI/CD pipelines, and operational readiness, ensuring reliable and efficient releases in cloud environments
- Drive monitoring, performance optimization, and reliability improvements for applications operating in the cloud

Angular

Python

SQL

Cloud

Architecture

- Components, services, modules
- Lifecycle hooks (ngOnChanges, ngOnDestroy)
- Template vs reactive forms
- Angular migration (v6 v16)
- Handling 3rd-party compatibility
- Standalone components vs modules
- State management (BehaviorSubject, NgRx)
- RxJS usage (switchMap, reactive flows)
- Data sharing across components
- Spinner/loading handling
- Dashboard UI (charts,



pagination, wizard forms)
- API integration with backend

• Angular vs React comparison

- FastAPI-based API development

- Backend service implementation
- PySpark data processing
- Data migration (EDW EDW)
- Data pipeline development
- Handling large datasets
- Data ingestion & preprocessing (image/audio)
- AI/ML model selection (precision, recall)
- Multi-agent LLM architecture
- Chatbot integration

• Backendfrontend integration

- SQL Server, PostgreSQL, MySQL, NoSQL

- Joins, GROUP BY
- CTEs vs Views
- Tables vs Views
- Window functions (LEAD, LAG)
- Ranking & time-series analysis
- Query writing for business problems
- Indexing & partitioning
- Query tuning (ClickHouse)

• Stored procedure optimization

- AWS (Lambda, API Gateway, ECS, ECR, LB)

- Azure (ADF, Databricks)
- Azure DevOps / TFS pipelines
- CI/CD (Jenkins, GitHub Actions)
- Docker & Kubernetes
- Deployment workflows
- Cloud data pipelines
- Managed AI services

• Monitoring, logging, alerts, reruns

- J D: tem design (vendor management system)

- Microservices architecture
- REST API design principles
- Real-time streaming vs APIs
- WebSockets, async queue processing
- Data architecture (Raw/Silver/Gold layers)
- Global DB design (manufacturing/fabs)
- Full-stack architecture (UI–API–DB)
- Frontend vs backend logic decisions
- Scalability & latency optimization
- RAG, embeddings, vector DBs
- LLM chunking strategies

• Requirement analysis & solution designJ

📌 Python Fullstack Developer (Hyderabad)
🏢 TechStar Group
📍 Hyderabad