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Tier-1 brand, common data-engineer role, and likely metro office increase competitive density.
Core data-engineering skills (AWS, PySpark, SQL, Snowflake) are highly transferable across industries.
Explicit 0-2 years plus required AWS, PySpark, Snowflake, CI/CD and containerization raises filtering strictness.
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Contribute to applications development including system enhancements, issue analysis, debugging, and scripting primarily using Python and PySpark.
Develop and maintain data engineering pipelines leveraging AWS services (EKS, S3, MWAA, IAM, VPC), containerization (Docker, Kubernetes), and CI/CD tools (preferably Harness).
Support data warehousing tasks involving Snowflake including data modeling, ingestion, and performance tuning, along with SQL programming.
0-2 years of relevant programming and application development experience.
Bachelor's degree or equivalent experience required.
Strong proficiency with core AWS services (EKS, S3, MWAA, IAM, VPC).
Hands-on experience with Python scripting, PySpark, Docker, Kubernetes (EKS), and SQL; CI/CD experience preferably with Harness.
Familiarity with building and optimizing data pipelines and workflows using AWS managed services.
Experience in cloud-native containerized environments and automated deployment pipelines.
Knowledge of data warehousing concepts and practical skills in Snowflake data platform is advantageous.