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Mid-level data role in Bangalore with common required skills increases applicant competition.
Data engineering skills (Python, Airflow, DBT, AWS) are highly transferable across industries.
Explicit 5+ years and many mandatory AWS, DBT, Airflow, and Python tool requirements make filtering strict.
Own design, development, and support of backend services, APIs, and ETL/ELT data pipelines using Python and AWS.
Manage and optimize cloud-native data workflows leveraging AWS services such as Lambda, Glue, ECS/EKS, and Airflow.
Lead automation and operational troubleshooting of complex ETL and production issues ensuring scalable, reliable data solutions.
5+ years of experience in backend development, data engineering, or cloud-native solutions.
Strong proficiency in Python with frameworks FastAPI, Flask, Django, Celery, SQLAlchemy.
Deep AWS knowledge including S3, Lambda, Glue, ECS/EKS, Fargate, SQS, SNS, EventBridge, EC2, Airflow.
Experience with both relational (PostgreSQL, MySQL, Redshift) and NoSQL (MongoDB) databases plus SQL expertise.
Experienced in managing and optimizing ETL pipelines and backend APIs in AWS cloud environments.
Proficient in containerization and cloud-native architectures using Docker and Kubernetes.
Demonstrates strong ownership with ability to independently troubleshoot, optimize production workflows, and collaborate across engineering and business teams.