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Mid-level data platform role, common skillset, metro locations, and 3-6 years amplifies competition.
Core data platform skills are highly transferable across industries despite insurance domain being only a nice-to-have.
Explicit 4+ years and multiple mandatory AWS, Snowflake, Airflow, SQL/Python, Terraform skills create strict shortlisting.
Build and maintain scalable and reliable AWS-based data platforms and pipelines to power analytics and data-driven products.
Provision, modify, and optimize data infrastructure components using Terraform and manage orchestration services like Airflow and containerized environments (Docker, Kubernetes/EKS).
Implement data quality checks, observability, access control, and cost-optimization within AWS and Snowflake ecosystems.
4+ years of experience in Data Platform Engineering.
Proficiency with AWS core services including S3, IAM, compute services, and cloud data warehouses like Snowflake.
Hands-on experience in SQL and Python for data transformation and pipeline development.
Working knowledge of Airflow (including managed services like MWAA) and familiarity with dbt for data transformations and testing.
Experienced in operating within AWS cloud infrastructure focused on data platform reliability and scalability.
Comfortable working in agile, cross-functional teams with senior engineers, analysts, and data scientists.
Familiarity with streaming/event-driven data systems (Kafka, Kinesis), ELT/ETL workflows, and infrastructure-as-code practices.