About the role

AI summarised

The Process Intelligence Engineer designs, builds, and maintains Industrial & Systems Engineering data modeling and analytics solutions to support data-driven decision-making across logistics, supply chain, and manufacturing operations. This role translates complex business questions into scalable reporting models and actionable insights for engineering and operations stakeholders.

EquipmentOnsiteBusiness Operations

Key Responsibilities

Design and develop reporting solutions in cross-functional teams to enable data-driven decisions for logistics, supply chain, and manufacturing.
Develop and maintain dashboards, analytical data models, and KPI frameworks using BI platforms.
Build scalable ETL data pipelines for ingestion, cleansing, integration, and transformation of large datasets from operational systems.
Perform ad-hoc statistical, diagnostic, and root-cause analysis using SQL and Python to support business investigations.
Interface with internal customers to gather requirements, translating business problems into reporting specifications and analytical outputs.
Create automated workflows to ensure the timely refresh and reliability of datasets, dashboards, and scorecards.
Generate technical documentation, business presentations, and stakeholder communications for operations and leadership.
Evaluate visualization and reporting technologies to recommend improvements in efficiency, data quality, and automation.

Requirements

Strong conceptual and hands-on expertise in data modeling, dashboard design, KPI definitions, process intelligence, and business analytics.
Proven ability to understand how BI integrates with operations, logistics, supply chain, and enterprise analytics ecosystems.
Working knowledge of engineering workflows, cloud data platforms, and SQL-based data warehouse systems.
Ability to translate business problems into technical reporting specifications and analytical outputs.
Strong understanding of best practices in reporting governance and BI lifecycle management.