Director, Data Engineering

Caterpillar Inc.•Mossville, IL

1d•Onsite

About The Position

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. Role Summary The Director of Data Engineering is a senior technology leader responsible for designing, building, and scaling the enterprise data engineering ecosystem that powers Cat Technology platforms. This role will lead the extension of the Data Platform to support the physical AI platform for machine and jobsite autonomy, ensuring high‑quality, well-architected, and reliable data products that enable analytics, insights, and downstream applications. The Director will set the vision for data design and architecture, oversee data acquisition and ingestion strategies, and lead the development of robust data engineering pipelines for transformation, quality, storage, and access. This role partners closely with business stakeholders, analytics, product, and various platform engineering teams to ensure data solutions are scalable, secure, and aligned to enterprise priorities.

Requirements

Decision Making and Critical Thinking: Knowledge of the decision-making process and associated tools and techniques; ability to accurately analyze situations and reach productive decisions based on informed judgment.
Effective Communications: Understanding of effective communication concepts, tools and techniques; ability to effectively transmit, receive, and accurately interpret ideas, information, and needs through the application of appropriate communication behaviors.
Software Engineering: Knowledge of software engineering; ability to deliver new or enhanced fee-based software products.
Software Reliability Management: Knowledge of software reliability management; ability to develop and use principles, methodologies and metrics that increase software product performance and reliability.
Agile Development: Knowledge of agile methodologies and the agile development lifecycle; ability to utilize formal agile methodologies, disciplines, practices and techniques for the delivery of new and enhanced applications.

Nice To Haves

10+ years of experience in data engineering, data architecture, or related roles, with at least 5 years in a people‑leading or senior leadership capacity.
Strategic thinker with the ability to balance long‑term vision and near‑term delivery.
Strong people leader who develops talent and builds high‑performing teams.
Strong experience designing and operating large‑scale data platforms and pipelines.
Deep understanding of data modeling, data warehousing, and modern data architectures.
Proven experience leading complex, cross‑functional initiatives in an enterprise environment.
Experience supporting multi‑platform or product‑based data ecosystems.
Hands‑on experience with cloud‑based data platforms, modern ETL/ELT frameworks, and data observability tools.
Familiarity with data governance, privacy, and security best practices.
Strong business acumen with the ability to align technical solutions to organizational outcomes.

Responsibilities

Define and own the data engineering strategy in support of Cat Technology platforms, including the data and AI platform.
Lead, mentor, and develop data engineers, architects, and technical leads to build high‑performing teams
Establish standards, best practices, and governance for data engineering, architecture, and lifecycle management
Design and oversee scalable, secure, and resilient data architectures across cloud and hybrid environments
Own data acquisition and ingestion strategies, including batch, streaming, and near‑real‑time pipelines
Oversee development of reliable, cost‑effective data pipelines with strong data quality, monitoring, and observability
Partner with product, analytics, platform, and business stakeholders to translate requirements into scalable data solutions