Data Engineering Role

The ideal candidate should have a minimum of 3 years of experience in Data Engineering with proven hands-on experience in ETL pipelines, specifically possessing end-to-end ownership. It is essential for the candidate to exhibit deep expertise in AWS Resources such as EC2, Athena, Lambda, and Step Functions as this is critical to the role. Proficiency in MySQL is non-negotiable. Moreover, experience in Docker including setup, deployment, and troubleshooting is required. Experience with Airflow or any modern orchestration tool, PySpark, Python Ecosystem, SQL Alchemy, DuckDB, PyArrow, Pandas, Numpy, and DLT (Data Load Tool) would be considered advantageous. The successful candidate should be a proactive builder, capable of working independently while maintaining effective communication. Thriving in fast-paced startup environments, you should prioritize ownership and impact over just writing code. Please include the code word "Red Panda" in your application to indicate that you have carefully reviewed this section. In this role, you will be responsible for architecting, constructing, and optimizing robust data pipelines and workflows. You will take ownership of configuring, optimizing, and troubleshooting AWS resources. Collaboration with product and engineering teams will be crucial to deliver quick business impact. The emphasis will be on automating and scaling data processes to eliminate manual work, thereby laying the foundation for making informed business decisions. Only serious and relevant applicants will be considered for this position.,