Job Summary

Lead Software Engineer (AWS, Snowflake ML Backend)

Position Overview

Job Title: Lead Software Engineer

Department: Data Analytics

The Lead Software Engineer drives the technical vision, execution, and quality of core software products. This role balances hands-on coding and technical leadership with deep architecture collaboration, partnering with enterprise architects, product managers, data scientists, and engineering teams to design secure, scalable, and high-performance distributed systems. Operating heavily within AWS and Snowflake, this leader will architect the backend services, robust data infrastructure, and automated MLOps workflows that power the productionization of machine learning models and analytical workflows to generate real-time predictions and actionable business insights.
Key Responsibilities
- ML Analytics Workflows Productionization
- Model Deployment: Architect and maintain reliable backend microservices to deploy, scale, and monitor machine learning models in production environments.
- Pipeline Orchestration:



Design robust batch and real-time analytical pipelines that ingest raw enterprise data, perform feature engineering, and output high-accuracy predictions.
- MLOps Governance: Establish continuous integration and continuous deployment (CI/CD) practices customized for ML infrastructure, including model versioning, registry, and drift tracking.
Cloud Data Architecture Collaboration
- AWS Framework Integration: Co-design cloud-native, distributed backend systems utilizing AWS managed services (such as SageMaker, Lambda, ECS/EKS, and Step Functions).
- Snowflake Optimization: Partner with Data Architects to build optimized storage, data views, and high-performance analytical queries within Snowflake to guarantee low latency for downstream insights.
- Data Security Lineage: Ensure strict data governance, access controls, and reproducible data validation protocols across both training pipelines and live execution layers.
Techn

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