TECH LEAD FOR NON-AUTHORING BACKEND LOGIC

Accountabilities: • Design, develop, and maintain backend services, data APIs, and serverless components supporting analytics and application workloads. • Build and operate event-driven architectures using AWS services such as S3, EventBridge, SNS/SQS, Lambda, Step Functions, and AWS Glue. • Develop and optimize ETL pipelines and data workflows to support near real-time and batch processing requirements. • Create and maintain scalable data structures, including dimensional models, schemas, partitioning strategies, and optimized warehouse solutions. • Enable analytics and reporting capabilities through Amazon QuickSight, including data preparation, semantic modeling, security configurations, and dashboard performance optimization. • Apply big data engineering best practices across cloud storage, data lakes, columnar formats, and large-scale analytics workloads. • Implement monitoring, logging, and alerting solutions using AWS CloudWatch, X-Ray, and related observability tools. • Collaborate with data engineers, data scientists, and product teams to translate business and analytics requirements into technical solutions. • Contribute to architecture decisions, technical reviews, cloud optimization strategies, and AWS best practice adoption. • Mentor engineers on serverless architectures, cloud-native development patterns, coding standards, and data application practices. Requirements: • 10+ years of hands-on experience building applications and services on AWS, ideally in backend engineering or cloud architecture roles. • Advanced proficiency in Python for backend development, ETL processes, and automation, including AWS Lambda and AWS Glue usage. • Strong experience with AWS serverless technologies, including Lambda, API Gateway, Step Functions, and event-driven integration patterns. • Proven experience designing and maintaining ETL pipelines using AWS Glue jobs, workflows, crawlers, and related data integration tools. • Strong SQL skills with experience working with analytical databases and data warehouses, particularly Amazon Redshift. • Solid understanding of data warehousing concepts, including dimensional modeling, fact and dimension design, slowly changing dimensions, partitioning, and indexing. • Experience with AWS big data analytics solutions such as S3-based data lakes, Parquet/ORC formats, Redshift Spectrum, Athena, or similar technologies. • Practical experience with business intelligence and data visualization tools, preferably Amazon QuickSight. • Understanding of AWS infrastructure fundamentals, including VPC, networking, IAM, encryption, security practices, and cost optimization. • AWS certification such as Solutions Architect, Data Analytics, Developer, or equivalent practical expertise is preferred. • Strong leadership, communication, and mentoring skills with the ability to collaborate across technical and business teams. Benefits: • Competitive total rewards package. • Opportunity to work on large-scale cloud, data, and analytics solutions. • Remote work flexibility. • Access to continuing education and professional training opportunities. • Opportunity to grow within a global technology organization. • Collaborative environment focused on innovation, learning, and technical excellence. • Ability to influence architecture decisions and contribute to impactful digital transformation initiatives. How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best!  Why Apply Through Jobgether?    Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.     #LI-CL1