Junior Data Engineer - Be the Spark That Ignites Innovation!

A beginner s mindset with 0-3 years of experience in data engineering or a related field. Strong hands-on experience with Python as a primary programming language. Familiarity with object-oriented programming (OOP) principles in Python. Proficiency in Python IDEs like Jupyter Notebook, PyCharm, or VS Code. Understanding of data serialization formats like JSON, Avro, and Parquet. Ability to write and maintain Python-based automation scripts for data workflows. Knowledge of version control systems like Git. Build scalable ETL pipelines to power our cutting-edge AI/ML models. Explore cloud platforms like AWS, GCP, or Azure to manage and process massive datasets. Shape the future of data with real-time processing frameworks like Kafka, Spark, or Flink. Collaborate with seasoned engineers and data scientists to unlock the hidden potential of data. Automate workflows with tools like Airflow, Luigi, and Prefect. Develop reusable Python scripts for data extraction, transformation, and loading (ETL). Implement unit tests and debug Python applications using tools like Pytest. Leverage Python libraries such as: Pandas: For data manipulation. NumPy: For numerical computations. PySpark: For distributed data processing. Scikit-learn: For basic machine learning tasks. Are you a data wizard who loves building scalable pipelines and solving complex data challengesJoin us at Neuralix.ai, where we craft AI-driven solutions that redefine industries. If data engineering is your playground and innovation is your fuel, we want you on our team! As a Junior Data Engineer, you ll work closely with experienced engineers to build foundational data engineering skills. This role is perfect for freshers or those early in their careers who are excited to learn, experiment, and grow in a supportive environment.