Senior Developer 2 for Non-Authoring Backend Logic

About the role

Backend engineer responsible for designing and building cloud-native, event-driven data and analytics services on AWS, with a focus on serverless application development, ETL pipelines, and enabling self-service analytics and reporting in Amazon QuickSight. The engineer will work closely with data, analytics, and product teams to deliver reliable, scalable data services and BI capabilities. Core Responsibilities Design and develop backend services and data APIs and other serverless components to support analytics and application workloads. Build and operate event-driven architectures that integrate S3, EventBridge, SNS/SQS, Lambda, Step Functions, and AWS Glue for near real-time and batch ETL workloads powering QuickSight dashboards and authoring. Implement robust ETL and data integration pipelines using AWS Glue (jobs, workflows, crawlers) to load, transform, and curate data in Amazon Redshift and the broader data warehouse environment. Model, optimize, and manage data structures (star/snowflake schemas, partitioning, distribution/sort keys) in Amazon Redshift and related data stores for performant SQL and BI queries. Enable and support Amazon QuickSight reporting and authoring, including data preparation, semantic modeling, row-level security, and performance tuning for dashboards and analyses. Apply big data analytics best practices for scalable storage and compute (e.g., S3-based data lakes, columnar formats like Parquet, pushdown, partition pruning). Design and implement monitoring, logging, and alerting for event-driven and serverless workloads using CloudWatch, X-Ray, and related services. Collaborate with data engineers, data scientists, and product teams to translate business and AI/analytics requirements into technical designs and working solutions. Contribute to architecture decisions, design reviews, and AWS best-practice adoption (security, IAM, networking, cost optimization, reliability). Mentor other engineers in serverless, data, and AI application patterns, coding standards, and cloud-native design.