Engineering Manager - Data Quality

Caterpillar

Quick summary

Work type
On-site
Location
Peoria, IL
Salary
$147,760–$240,110 / yr
Posted
7 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $184k
This role $194k
$132k most similar roles pay here $252k

This role pays more than 58% of similar roles. Most pay $143,248–$224,250 — the shaded band above. At the midpoint, this role pays about $194k versus about $184k for comparable roles.

Based on 239 similar postings.

Employer

About Caterpillar

Caterpillar Inc. is the world''s largest manufacturer of construction and mining equipment, diesel and natural gas engines, industrial gas turbines, and diesel-electric locomotives. Industry: Heavy Equipment & Manufacturing

Caterpillar currently has 25 open roles on FindRole.

Listed pay typically runs $128,470–$208,770 across 25 roles with salary data.

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View all roles at Caterpillar

At a glance

TL;DR · Engineering Manager - Data Quality

The Engineering Manager – Data Quality leads a high-performing team responsible for maintaining the accuracy and reliability of enterprise connectivity data across platforms, combining technical leadership with people management. This role involves defining data quality strategies, establishing standardized frameworks, and implementing scalable validation solutions while ensuring compliance with governance standards. The manager will drive AI/ML adoption for automated data checks and predictive monitoring, build a skilled team of data engineers and analysts, and collaborate closely with various teams to ensure data readiness for new programs and releases. Ideal candidates have 8+ years of experience in software/data engineering, including leadership roles, with expertise in data quality, governance, and cloud platforms like Azure or AWS. Additional skills include hands-on experience with ETL/ELT frameworks, metadata management tools, and CI/CD pipelines, as well as familiarity with regulated environments and streaming data platforms.

What you'll do

  • Define and lead enterprise data quality strategy aligned with business objectives.
  • Establish standardized data quality frameworks, rules, and metrics for accuracy and consistency.
  • Design scalable validation solutions and embed data quality controls in pipelines.
  • Drive adoption of AI/ML techniques for automated data profiling and anomaly detection.
  • Build and mentor a team of data quality engineers to foster continuous improvement.

What we're looking for

  • 8+ years of experience in software/data engineering, including leadership roles
  • Strong background in data quality, governance, and data engineering ecosystems
  • Hands-on expertise with data pipelines, ETL/ELT frameworks, and cloud platforms
  • Experience implementing automated testing and validation frameworks for data systems
  • Bachelor’s or Master’s degree in Computer Science, Software Engineering, Data Engineering, or related field
  • Knowledge of data modeling, metadata management, and data lineage tools
  • Familiarity with AI/ML-based data quality monitoring and streaming data platforms

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