This role is for one of the Weekday's clients
Min Experience: 5 years
Location: Bengaluru
JobType: full-time
As a Python Data Engineer / Backend Engineer, you will be responsible for designing efficient data workflows that process large volumes of data stored in cloud environments. The role involves working extensively with AWS services such as S3, Lambda, and RDS, while applying Python techniques like async programming, multithreading, and multiprocessing to solve performance bottlenecks. You will also contribute to building reliable APIs, implementing caching strategies, and ensuring data quality through validation and error handling. This role assesses not just implementation skills, but also architectural thinking and the ability to evaluate and improve existing code.
Requirements
Key Responsibilities
- Design memory-efficient and high-performance data processing solutions for large datasets (1GB+ CSV and similar files) using Python
- Build cloud-native data pipelines that read and write data from AWS S3 using AWS Lambda
- Implement data validation and cleansing logic to ensure accuracy and consistency
- Develop scalable ETL workflows to extract data from S3, transform it based on business logic, and load it into RDS
- Optimize API data fetching by implementing concurrent and asynchronous processing using async/await
- Design and implement caching mechanisms for cloud-based database-backed APIs to improve response times and reduce load
- Decide and implement appropriate concurrency models using multithreading or multiprocessing based on workload characteristics
- Identify performance bottlenecks and recommend architectural or code-level improvements
- Review Python code to identify errors, inefficiencies, and missing best practices
- Apply logging, exception handling, and monitoring best practices for production-grade systems
- Ensure solutions are scalable, cost-effective, and aligned with cloud-native design principles
What Makes You a Great Fit
- Strong experience in Python for backend or data engineering use cases
- Hands-on experience with AWS Lambda, S3, and RDS
- Solid understanding of ETL concepts and data pipeline design
- Experience implementing async programming and concurrent API handling
- Ability to reason about performance trade-offs between multithreading and multiprocessing
- Familiarity with caching strategies for APIs and cloud databases
- Strong understanding of memory management and efficient file processing
- Ability to review existing Python code and identify bugs, anti-patterns, and missing best practices
- Knowledge of cloud scalability, cost optimization, and serverless architectures
- Strong problem-solving skills with an architectural mindset
- Clear communication skills to explain technical decisions and improvements
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