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Principal Engineer, Operational Intelligence

Remote / Online - Candidates ideally in
Fort Lauderdale, Broward County, Florida, 33301, USA
Listing for: ASR Group
Remote/Work from Home position
Listed on 2026-10-30
Job specializations:
  • IT/Tech
    Business Intelligence, AI Business & Operations, Data Analyst, Data Engineering
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below
Principal Engineer, Operational Intelligence

Location:

Home Office, FL, US

Date:
Oct 26, 2026

The ASR Group® family of companies make up the world’s largest refiner and marketer of cane sugar. The companies produce a full line of grocery, industrial, food service and specialty sweetener products. Across North America, ASR Group® companies operate five sugar refineries, located in California, Maryland, Louisiana, Canada and Mexico. In Europe, ASR Group® companies operate sugar refineries in the United Kingdom, Portugal, and, with a joint venture partner, Italy.

The companies also farm sugarcane and own sugar mills in Mexico and Belize. The ASR Group® portfolio includes the leading brands Domino®, C&H®, Florida Crystals®, Redpath®, Tate & Lyle®, Lyle's®, Sidul® and Whitworths®. ASR Group® companies also produce and market Tellus®, a single-use, compostable tableware and food service product made from plant fibers, including sugarcane.

OVERVIEW

The Principal Engineer, Operational Intelligence provides enterprise leadership for the Operational Intelligence discipline across ASR Group refinery operations. The role is responsible for transforming operational information into insights, recommendations, predictions, and actions that improve refinery performance. This position establishes the strategy, standards, governance, technology roadmap, and technical direction for the discipline, which for the purposes of this document means analytics and data science, process and performance intelligence, predictive and prescriptive analytics, optimization, decision support, and operational performance modeling.

Operational Intelligence output is advisory by default. Where an analytical result is to be applied automatically, the write path is designed and owned by Controls under Management of Change. This role is accountable for ensuring intelligence solutions are focused on measurable operational value and support reliable, resilient, secure, and stable refinery operations.

DETAILED ROLES & RESPONSIBILITIES
  • Provide enterprise leadership and capability ownership for the Operational Intelligence discipline across refinery sites.
  • Develop and maintain the Operational Intelligence strategy, standards, technology roadmap, architecture, and governance model.
  • Own the enterprise Operational Context Standard: the asset model, measurement vocabulary, semantic classification of process points, engineering units, naming conventions, and metadata quality expectations that make refinery data usable for analysis. Specify this standard as a data contract that EIC and OT Infrastructure implement in the platforms they own.
  • Establish and chair the Operational Intelligence governance forum, with a published intake path for operational problems, a prioritization method, a decision cadence, and a defined escalation route to the Sr. Director, Digital Transformation, OT & Controls when discipline priorities conflict.
  • Lead, coach, and develop the central team; set priorities, review technical quality, support skill development, and build a sustainable talent pipeline across the central team and site-based analysts.
  • Partner with refinery and functional leaders to identify, prioritize, and define high-value operational problems that can be addressed through the discipline.
  • Translate operational needs into a governed portfolio of intelligence initiatives with clear objectives, ownership, value measures, and adoption plans.
  • Lead the development, deployment, and sustainment of performance analytics, predictive capabilities, optimization opportunities, decision-support tools, and operational performance models.
  • Define and own the production lifecycle for deployed intelligence solutions: where each solution executes, who monitors it, how model…
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