At least 3 years of professional experience in Data Engineering
Demonstrated end-to-end ownership of ETL pipelines
Deep, hands-on experience with AWS services: EC2, Athena, Lambda, and Step Functions (non-negotiable)
Strong proficiency in MySQL (non-negotiable)
Working knowledge of Docker: setup, deployment, and troubleshooting

Highly Preferred Skills:

Experience with orchestration tools such as Airflow or similar
Hands-on with PySpark
Familiarity with the Python data ecosystem: SQLAlchemy, DuckDB, PyArrow, Pandas, NumPy
Exposure to DLT (Data Load Tool)

Ideal Candidate Profile:

The role demands a builders mindset over a maintainers. Independent contributors with clear, efficient communication thrive here. Those who excel tend to embrace fast-paced startup environments, take true ownership, and are motivated by impactnot just lines of code. Candidates are expected to include the phrase Red Panda in their application to confirm theyve read this section in full.

Key Responsibilities:

Architect, build, and optimize scalable data pipelines and workflows
Manage AWS resources end-to-end: from configuration to optimization and debugging
Work closely with product and engineering to enable high-velocity business impact
Automate and scale data processesmanual workflows are not part of the culture
Build foundational data systems that drive critical business decisions

Compensation range: 8.412 LPA (fixed base), excluding equity, performance bonus, and revenue share components.

Industry

Technology, Information and Internet

Employment Type

Full-time

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Data Engineer