Website Hitachi
Data Analyst – Hitachi Energy (Global Engineering Center)
Opportunity Overview
Engineering Analytics & Automation Operations Workflow
The Data Analyst at Hitachi Energy operates within an international engineering team, transforming enterprise data from SAP and engineering platforms into automated performance metrics, resource forecasts, and strategic leadership dashboards:
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│ 1. Enterprise Ingestion & SAP Cleansing │ ➔ Extract & validate operational data across SAP, SQL databases & engineering systems
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│ 2. Engineering Utilization Modeling │ ➔ Analyze productivity, capacity, workload data & delivery performance metrics
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│ 3. Power Platform & Workflow Automation │ ➔ Build automated flows & low-code apps via Power Automate & Power Apps to streamline reporting
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│ 4. BI Dashboarding & Executive Alignment │ ➔ Deploy Power BI scorecards to track engineering KPIs & present insights to global leaders
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Key Responsibilities
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Data Analytics & BI Reporting: Extract, clean, and analyze datasets across enterprise systems (SAP, SQL) to design dashboards, scorecards, and automated Power BI reports.
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Engineering Performance Tracking: Measure engineering utilization, productivity, workforce capacity, and project delivery schedules to optimize resource allocation and hiring forecasts.
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Digitalization & Power Platform Automation: Deploy automated workflows and applications using Microsoft Power Platform (Power BI, Power Automate, Power Apps) to eliminate manual reporting tasks.
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Data Governance & Data Quality: Standardize metrics across global engineering functions, maintaining dataset documentation, audit processes, and enterprise data hygiene.
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Global Stakeholder Collaboration: Interface with Engineering Managers, Operations, Finance, and international team leads to translate complex operational needs into quantitative frameworks.
Qualification Matrix & Technical Skill Stack
Core Requirements
Key Focus Areas for Interview Preparation
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Power Platform & Automation Integration: Be ready to demonstrate how Power BI, Power Automate, and Power Apps work together to automate manual data collection and report distribution.
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SQL & SAP Data Management: Practice writing SQL queries for joining, aggregating, and cleansing operational data sourced from enterprise ERP systems like SAP.
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Engineering Resource & Productivity Metrics: Review concepts surrounding utilization rates, capacity forecasting, and operational project delivery KPIs in manufacturing or energy engineering settings.
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