Engineer, Senior Operational Analytics

Enterprise Products • Houston, TX

1d

About The Position

The Sr. Operational Analytics Engineer partners closely with internal customers across Operations & Technical Services — including Operations Engineers, Reliability Engineers, Process Engineers, and field/plant Operations — to identify business problems and translate them into data‑driven solutions. This role is responsible for developing analytic tools and workflows that leverage Spotfire, Seeq, and other platforms to extract insights from operational and business data. The engineer will also collaborate with technical teams such as Data Science, Data Engineering, and IT to ensure the right data structures, pipelines, and models are in place to support analytical needs. This position requires a blend of domain expertise, strong analytical capability, and the ability to work cross‑functionally to deliver solutions that improve operational efficiency, reliability, and cost performance.

Requirements

• Strong problem‑solving skills and experience analyzing operational data is required.
• Experience with Spotfire, Seeq, or equivalent operational analytics tools is required.
• Bachelor’s degree in Mechanical, Chemical, Electrical, or a related Engineering discipline is required.
• Minimum 5+ years of experience in pipeline or plant operations engineering; other relevant operational experience may be considered.
• Strong communication skills with the ability to troubleshoot quickly and articulate root cause is required.
• Ability to work effectively in a small team environment.

Nice To Haves

• Experience with optimization techniques or mathematical algorithms is a plus.
• Master of Applied Data Science, Applied Data Analytics, or similar advanced technical degree is preferred.

Responsibilities

• Engage with internal customers (like Operations or Reliability) to define business problems and translate requirements into data‑driven analytic solutions.
• Build analytical tools and dashboards using Seeq, Spotfire, DataPARC, or PowerBI to support operational reliability and performance improvements.
• Partner with Data Science and Data Engineering to coordinate the appropriate data architecture, pipelines, and modeling approaches.
• Conduct operational root‑cause analyses using Seeq, DataPARC, or related tools.
• Work independently while also collaborating within small, cross‑functional teams.
• Facilitate improvement efforts across multiple functional groups; coordinate regular status meetings to drive progress.
• Provide clear written and verbal project updates, including insight summaries and recommendations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level