Lead Digital Project Manager (Analytics Quality Manager)

Caterpillar Inc.•Peoria, 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. Cat Digital is the digital and technology arm of Caterpillar Inc., leveraging the latest technologies to build industry leading digital solutions for our customers and dealers. With over 1.5 million connected assets worldwide, our teams use data, technology, advanced analytics, telematics, and AI capabilities to help our customers build a better, more sustainable world. This role leads the planning, execution, and continuous improvement of analytics quality and KPI reporting initiatives. It involves working hands‑on with data, dashboards, and stakeholders to ensure analytics outputs are accurate, consistent, and decision‑ready for cross‑functional leadership and analytics execution partners. Caterpillar Inc. is the world’s leading manufacturer of construction and mining equipment, off-highway diesel and natural gas engines, industrial gas turbines and diesel-electric locomotives. For nearly 100 years, we’ve been helping customers build a better, more sustainable world and are committed and contributing to a reduced-carbon future. Our innovative products and services, backed by our global dealer network, provide exceptional value that helps customers succeed.

Requirements

Extensive knowledge of planning techniques supporting analytics quality, KPI reporting, and decision‑support initiatives aligned to business priorities.
Extensive experience managing multiple analytics quality initiatives, including prioritization, dependencies, risks, and delivery.
Extensive ability to assess data quality issues, evaluate trade‑offs, and prioritize work based on impact, trust, and timeliness.
Extensive experience ensuring accurate, consistent, decision‑ready KPIs, dashboards, and reports.
Working knowledge supporting analytics reporting solutions, dashboards, and guided insight applications.
Working knowledge monitoring progress, surfacing risks, and communicating quality outcomes.
Extensive experience leading analytics quality and reporting initiatives across cross‑functional teams.
Working knowledge ensuring alignment with data governance, reporting standards, and IT policies.
Bachelor’s degree or equivalent experience in computer science, analytics, information systems, or related fields.
Extensive experience partnering with software engineering teams in agile environments (typically 8+ years).
Strong hands‑on experience with analytics quality, KPI definition, validation, and executive reporting (typically 5+ years).
Strong SQL proficiency (Snowflake) for metric validation and issue investigation.
Experience with Power BI dashboards and guided analytics applications (e.g., Streamlit).
Familiarity with applying AI or generative‑AI capabilities to accelerate analytics quality definition and oversight.
Proven ability to translate ambiguous questions into trusted, decision‑ready insights.
Strong communication and stakeholder‑management skills.

Responsibilities

Lead analytics quality initiatives, including KPI definition, validation, reporting enhancements, and quality monitoring.
Manage execution across multiple analytics quality workstreams, balancing priorities, dependencies, and timelines.
Evaluate analytics deliverables (KPIs, dashboards, reports) to ensure accuracy, reliability, and business alignment.
Monitor results for deviations and ensure adherence to analytics quality standards, governance, and processes.
Identify quality risks and implement mitigation plans to protect decision accuracy and stakeholder trust.
Communicate quality status, risks, and improvements with business, analytics, and engineering stakeholders.