AWS Fullstack Data Engineer

Job Overview:We are seeking an experienced and visionary Senior Full-Stack Data Engineer to lead the architecture, development, and optimization of a next-generation data platform. This is a critical role for an individual with up to 15 years of deep data engineering expertise, capable of driving technical direction, mentoring team members, and delivering high-impact solutions in a fast-paced project environment..Key Responsibilities:Data Pipeline Development & ManagementIngestion & Transformation: Design, build, and optimize high-volume data ingestion and transformation jobs using tools like dbt Core, AWS Glue, ensuring data quality and integrity.Workflow Orchestration: Develop and maintain sophisticated data pipelines using orchestrators such as Dagster, focusing on modularity and reusability.Streaming & Real-time Integration: Implement and manage real-time data flows utilizing Confluent platforms or native AWS streaming services (e.g., Kinesis) for immediate data availability.Data Security and Privacy: Data Anonymization, Compliance with RegulationsAWS Architect development for Data PipelineBe well versed with DataOps and DevOps fundamentalsAssist and drive the Data Ecosystem Management & MonitoringHas experience with containerization and orchestration, specifically AWS ECS/ EKS.Infrastructure as Code (IaC): Can help with development and maintenance of some cloud foundation using IaC tools to ensure immutable, repeatable, and scalable deploymentsOpen Table Formats & Management: Implement and maintain the Iceberg open table format, utilizing tools for efficient schema evolution and data management.Compute Engine Optimization: Optimize query performance and cost efficiency across our primary compute engines: Snowflake, Amazon Redshift, and AWS Athena.Observability & Monitoring: Integrate comprehensive monitoring and observability into all pipelines using Splunk to ensure high availability, rapidly identify bottlenecks, and troubleshoot production issuesCandidate Profile:15+ Years of hands-on, progressive experience in Data Engineering, Data Architecture, or a closely related Full-Stack Data roleDeep conceptual understanding of core data engineering principles, ETL/ELT patterns, and metadata managementProven track record of building and managing petabyte-scale data infrastructure in a cloud-native environmentInsurance industry experience is mandatory.Tools:Cloud Environment: AWS (S3, IAM, VPC, etc.)Experience with Talend, dbt Core, Iceberg, AWS Glue Catalog, Snowflake, Redshift, Athena, Splunk, AWS streaming services, GitStrong SQL, Pyspark and Python