Principal Consultant Engineer (Consulting: Asset/Reliability Background)

Sao Paulo; Rio de JaneiroSenior8-10 years

The driving force behind our success has always been the people of AspenTech. What drives us, is our aspiration, our desire and ambition to keep pushing the envelope, overcoming any hurdle, challenging the status quo to continually find a better way. You will experience these qualities of passion, pride and aspiration in many ways — from a rich set of career development programs to support of community service projects to social events that foster fun and relationship building across our global community.

The Role

We are looking for a Principal Consultant to join our APM Professional Services team. You will lead the implementation of predictive maintenance and analytics solutions that help industrial clients improve asset reliability, reduce downtime, and optimize maintenance strategies. This is a highly customer-facing role requiring a combination of engineering expertise, data analytics, and consulting leadership.

Your Impact

Delivery consulting services including solution design, implementation, training, and advisory, primarily for Mtell (with exposure to Fidelis and ProMV).
Lead end-to-end deployment of predictive maintenance solutions, from data onboarding and modeling to production rollout and adoption.
Design and integrate data-driven decision systems using industrial data sources (e.g., historians, databases).
Translate asset knowledge and data analysis into effective monitoring strategies to detect anomalies and predict failures.
Collaborate with product management and client teams to deliver projects on time, scope, and budget.
Advise customers on embedding analytics into daily operations to drive measurable business impact.
Continuously improve solution performance by refining models and increasing trust in analytics outputs.
Build strong client relationships and identify opportunities for service expansion

What You'll Need

Experience

8–10 years in industrial environments (oil & gas, chemicals, mining)
Background in Mechanical, Chemical, Electrical, or Industrial Engineering
Experience in reliability, maintenance, or operations

Data & Analytics

Strong experience with industrial time-series data (data quality, signal validation, pattern recognition)
Experience with predictive or condition monitoring models

Reliability Knowledge

Understanding of failure modes, maintenance strategies, and root cause analysis (FMEA)
Knowledge of common industrial assets: rotating and static equipment

Technology