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Responsibilities and Requirements:
- Proficient in data manipulation and analysis using data frames and series.
- Experience with data cleaning, merging, reshaping, and aggregation.
- Knowledge of handling missing data, filtering, sorting, and applying functions to datasets.
- REST API:
- Experience in making GET and POST requests using libraries like requests.
- Ability to fetch, process, and handle JSON responses effectively.
- Knowledge of error handling, authentication (e.g., auth), and API rate limiting.
- Data structures in Python:
- In-depth knowledge of Python's built-in data structures: lists, tuples, dictionaries, sets, and arrays.
- Proficiency in implementing custom data structures using classes, methods, and functions.
- Regular Expression:
- Proficient in pattern matching, text searching, and data validation.
- Experience with reading from and writing to files (text, CSV, JSON).
Additional Details:
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Job function: Information Technology
- Industries: IT Services and IT Consulting
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About the Role:
Data Engineer - Enterprise Data Operations Analyst
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