Lead Software Engineer

Caterpillar•Irving, TX

1d•$126,000 - $204,720•Onsite

About The Position

Your Work Shapes the World at Caterpillar Inc. 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. We are seeking a highly skilled Software Engineering to lead our AI Accelerator within the Strategic Procurement and Planning Division (SPPD). This role will be partnered with the enterprise AI Accelerator mission team and business process experts to identify opportunities to develop AI based solutions to improve process efficiency. The AI accelerator role will deliver innovation by exploring emerging digital technologies and AI-driven solutions that address high-priority planning, supply chain and procurement business needs. In a small, working team, this role will act as a rapid prototyping and experimentation hub, validating proofs of concept for enterprise scaling and adoption. The ideal candidate will possess deep expertise in Big Data, Data Warehousing, real-time data movement, and Snowflake-based architecture. You will architect and deliver scalable, secure, and intelligent data platforms that enable advanced analytics, AI, and digital twin capabilities across global manufacturing ecosystems.

Requirements

Proven experience in Big Data processing and Data Warehousing.
Good understanding of AI concepts and latest developments (Gen AI, MCP, ATA, etc.).
Deep expertise in Snowflake, SQL, NoSQL, and distributed data systems.
Expertise in building end-to-end near real-time data pipelines for OLTP & OLAP.
Strong architecture exposure for building robust, scalable Data Platforms.
Strong analytical skills and solid knowledge of computer science fundamentals.
Deep exposure to Azure and AWS cloud platforms.
Bachelor’s or master’s degree in computer science, Engineering, or related field.
10+ years of experience in data engineering, with at least 2+ as team lead
Excellent communication, leadership, and stakeholder management skills.
This position requires working onsite five days a week.

Nice To Haves

Experience with Snowflake Cortex for rapid prototyping of AI solutions
Knowledge of process automation solutions such as Bizagi and Regrello
Experience with data transformation tools (dbt, Apache Spark, Azure Data Factory).
Experience building production-ready AI solutions
Familiarity with modern data visualization and BI tools (e.g., Power BI, Tableau, Looker).

Responsibilities

Provide thought leadership on methodology to identify high value opportunities to automate processes and improve employee efficiency through the use of AI technologies.
Lead workshops and design sessions on high value use cases for AI and process automation
Foster a culture of technical excellence, collaboration, and continuous learning.
Drive Agile practices to rapidly create prototypes that lead to a robust production solution
Designing, creating, deploying, and sustaining software solutions on a large scale.
Implementing application architectural patterns, including but not limited to MVC, Microservices, and Event-driven architectures.
Utilizing CI/CD tools such as Azure DevOps,
Deploying and managing software on public cloud platforms like AWS or Azure.
Collaborating within an Agile framework, preferably following Scrum methodologies.
Other AWS services like Lambda, cloud formation, cloud watch, S3.
Good working knowledge on Python modules like Pandas, Numpy, multithreading, requests, etc
Possess a solid understanding of version control systems, with a particular focus on GIT.
High Proficiency with SQL.
Lead the development of robust data pipelines for ingestion, transformation, and delivery using Snowflake, dbt, and cloud-native tools.
Optimize data storage, retrieval, and processing for performance, reliability, and cost-efficiency.
Implement data quality frameworks, lineage tracking, and schema evolution strategies.
Partner with subject matter experts, and business leaders to understand requirements and deliver impactful data solutions.
Document a technical solution design based on high level requirements from process and business experts
Communicate technical concepts to non-technical audiences and influence strategic decisions.