Python Developer

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Develop, test, and maintain scalable data processing pipelines using PySpark.
Collaborate with data scientists and analysts to understand data requirements and translate them into technical specifications.
Design and implement efficient data models and storage solutions.
Optimize existing PySpark applications for performance and scalability.
Write clean, maintainable, and efficient code following best practices in software development.
Conduct code reviews and provide constructive feedback to team members.
Troubleshoot and resolve issues in data processing workflows and applications.
Stay updated with the latest trends and technologies in data engineering and big data processing.

Proven experience as a Python Developer, specifically with PySpark.
Must have 10+ years of industry experience.
Strong understanding of data structures, algorithms, and software design principles.
Experience with big data technologies such as Hadoop, Spark, or similar frameworks.
Familiarity with data warehousing concepts and ETL processes.
Experience working with agile methodologies and SDLC processes would be preferred.
Must have AI/ ML experience with banking and financial services domain.
Knowledge of performance tuning data intensive applications
Expertise in functional and object-oriented programming, specifically in Python
Experience in databases (relational/document/etc.) including NoSQL databases
Strong in Algorithms and Data Structures
Experience building distributed and scalable complex services as well as robust micro services
Experience in writing unit tests in pytest or unittest
Working knowledge of CI/CD pipelines and automation
Strong sense of ownership, urgency, and drive
Experience in large scale enterprise application implementation
Proficient in SQL and experience with relational databases (e.g., PostgreSQL, MySQL).
Excellent communication and teamwork abilities.
Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) is a plus.