Tech Lead for Non-Authoring Backend Logic

Tech Lead for Non-Authoring Backend Logic

AWS Backend Lead

Location: Remote / Hybrid

Experience Level: Lead (10+ years)

Summary

Backend Lead 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.

Requirements:

• Strong hands-on experience (10+ Years) building applications and services on Amazon Web Services (AWS), ideally in a cloud application architect or backend engineer capacity.
• Advanced proficiency in Python for backend development, ETL, and automation (including use within AWS Lambda and AWS Glue jobs).
• Proven experience with serverless computing on AWS, including Lambda, API Gateway, Step Functions, and event-driven integration patterns.
• Solid experience designing and maintaining ETL pipelines and data workflows using AWS Glue (jobs, workflows, and crawlers) and related data integration tooling.
• Strong SQL skills and experience working with analytical databases and data warehouses, especially Amazon Redshift.
• Practical knowledge of data warehousing concepts (dimensional modeling, fact/dimension design, slowly changing dimensions, data partitioning, and indexing).
• Experience with big data analytics workloads on AWS (S3-based data lakes, Parquet/ORC, Redshift Spectrum, Athena, or similar).
• Hands-on experience with Business Intelligence (BI) and data visualization tools, with a preference for Amazon QuickSight (dataset design, dashboards, security).
• Understanding of cloud infrastructure fundamentals (VPC, subnets, networking, IAM, encryption, security best practices) in AWS.
• At least one relevant AWS certification (e.g., Solutions Architect, Data Analytics, Developer, or similar) or equivalent practical expertise.

We offer you a competitive total rewards package, continuing education & training, and tremendous potential with a growing worldwide organization.

DISCLAIMER:

Nothing in this job description restricts management's right to assign or reassign duties and responsibilities of this job to other entities; including but not limited to subsidiaries, partners, or purchasers of Alight business units.

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Experience Level

Senior Level