Lead Software Engineer (AWS, Snowflake & ML Backend)

- Snowflake Competency: Deep proficiency in advanced SQL, Snowflake warehousing, data modeling, and performance tuning for massive, complex analytic datasets. - Programming Skills: Strong programming background (e.g., Python) specialized in deploying scalable backend systems, REST/gRPC endpoints, and handling data pipelines. - Soft Skills: Exceptional communication, stakeholder management, and the ability to build consensus across multi-disciplinary technical teams.

- AWS Mastery: Hands-on expertise building architectures across the AWS ecosystem, specifically managing compute, storage, and serverless workflow orchestration. - Snowflake Competency: Deep proficiency in advanced SQL, Snowflake warehousing, data modeling, and performance tuning for massive, complex analytic datasets. - Programming Skills: Strong programming background (e.g., Python) specialized in deploying scalable backend systems, REST/gRPC endpoints, and handling data pipelines.

When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Job Description: 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.

Job Description: 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.

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. Technical Leadership & Mentorship Hands-On Development: Write clean, efficient, and secure code, actively contributing to critical components and complex backend feature development. Code Quality & Standards: Champion engineering excellence by setting and enforcing coding standards, conducting thorough code reviews, and establishing robust testing strategies. Team Guidance: Provide hands-on mentorship, technical coaching, and constructive feedback to junior and mid-level software engineers on the team.

Qualifications & Skills Experience: 8+ years of professional software development experience, with a solid focus on building data-intensive applications or ML backend infrastructure. - AWS Mastery: Hands-on expertise building architectures across the AWS ecosystem, specifically managing compute, storage, and serverless workflow orchestration. - Snowflake Competency: Deep proficiency in advanced SQL, Snowflake warehousing, data modeling, and performance tuning for massive, complex analytic datasets.