The Python Data Engineer role at the company requires proficiency in core Python concepts, including data types, variables, operators, control structures, functions, classes, modules, exceptions, and file handling. Familiarity with built-in data structures like lists, tuples, dictionaries, sets, and strings is also essential.
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Key Responsibilities:
- Web Frameworks: Knowledge of Python web frameworks (e.g., Flask, FastAPI, Pyramid) to create web applications, including skills in routing, templating, database integration, authentication, and testing.
- Object Relational Mappers (ORMs): Ability to use ORMs (e.g., SQLAlchemy, Django ORM) for database interaction through Python objects. This includes defining models, performing CRUD operations, querying data, and handling transactions.
- Data Science and Machine Learning: Skills in data science and machine learning are crucial. Proficiency in libraries such as NumPy, Pandas, SciPy, Scikit-learn, TensorFlow, and PyTorch for data analysis, manipulation, visualization, and modeling is required, alongside a good understanding of statistics, machine learning, and deep learning concepts.
Other Skills:
- Debugging and Testing: Capability to use debugging tools and techniques, including logging, breakpoints, unit testing, and integration testing.
- Version Control: Familiarity with version control systems like Git to manage code and collaborate with other developers, including creating branches, committing changes, and handling merge conflicts.
- Communication and Teamwork: Strong communication skills for effective collaboration with clients, stakeholders, and colleagues. This includes writing clear documentation and adhering to coding standards and best practices.
