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Mid-level metro role with a generic title and common AWS/Snowflake/Python skills increases candidate density.
Cloud data engineering skills (AWS, Snowflake, Python) are highly transferable across industries.
Explicit 3–6 years requirement plus mandatory AWS, Snowflake, and Python skills create strict technical filters.
Design, develop, and maintain scalable, secure data pipelines using AWS, Snowflake, and Python to support business reporting, analytics, and AI/ML use cases.
Build and optimize end-to-end data engineering solutions including data ingestion, transformation, validation, storage, and consumption layers with focus on performance and cost efficiency.
Implement data quality frameworks, perform root cause analysis for data incidents, and develop automation to improve platform reliability and operational efficiency.
3 to 6 years of professional experience in data engineering or related roles.
Strong hands-on experience with AWS services (S3, Lambda, Glue, Airflow, IAM, EventBridge) and advanced proficiency in Snowflake data platform.
Proficient programming skills in Python and strong SQL/database design knowledge.
Bachelor's degree in Engineering (B.Tech) mandatory; Snowflake or AWS data engineer certifications preferred.
Experienced in building scalable, production-grade cloud data pipelines with a focus on AWS and Snowflake ecosystems.
Capable of end-to-end ownership including design, monitoring, and troubleshooting in fast-paced, agile environments.
Comfortable working in dedicated onsite role (Kurla, India) within IST work hours, with strong documentation and knowledge transfer discipline.