Senior Data Analyst – Azure Analytics (Manufacturing Sector)

Overview

We are seeking an experienced Senior Data Analyst with strong expertise in Azure Analytics and Microsoft data technologies, specifically within a manufacturing environment. This role will drive data-led decision-making across production, supply chain, quality, maintenance, and operational excellence functions. The ideal candidate understands both advanced analytics and the complexities of modern manufacturing, including machine data, process optimization, OEE, and IIoT-driven insights.

Key Responsibilities

Manufacturing-Focused Data Analysis

• Analyze production, quality, and operational datasets to identify inefficiencies, cost-saving opportunities, and process improvements.
• Develop analytical models to optimize OEE (Overall Equipment Effectiveness), throughput, scrap rates, downtime tracking, and resource utilization.
• Apply statistical and predictive techniques to anticipate equipment failures, quality deviations, and supply chain disruptions.
• Partner with production, engineering, and supply chain stakeholders to translate manufacturing challenges into analytical solutions.

Azure Analytics & Data Engineering

• Build and maintain scalable data pipelines using Azure Data Factory and Azure Synapse Pipelines to ingest data from MES, ERP, SCADA, and IIoT platforms.
• Contribute to the design and optimization of manufacturing data architectures, including data lakes (ADLS Gen2), warehouses (Synapse), and Microsoft Fabric workspaces.
• Support integration of real-time and near-real-time operational data from sensors, controllers, and machine telemetry.

Business Intelligence & Visualization

• Develop and maintain high-impact Power BI dashboards tailored for plant leadership, operations, maintenance, and quality teams.
• Create visually intuitive reporting that enables monitoring of production KPIs, downtime causes, cycle times, bottlenecks, yield performance, and inventory health.
• Ensure data models reflect manufacturing processes accurately and are optimized for performance and governance.

Data Governance & Quality

• Establish data validation frameworks for production and quality systems, ensuring traceability, accuracy, and compliance.
• Support enterprise data governance with Microsoft Purview, focusing on metadata, lineage, and sensitive manufacturing data classification.
• Promote consistent data standards across plants, systems, and business units.

Stakeholder Engagement & Leadership

• Act as a strategic advisor to operations, engineering, supply chain, and quality leadership teams.
• Communicate analytical findings clearly to non-technical stakeholders and plant personnel.
• Lead cross-functional workshops to identify manufacturing pain points and opportunities for data-driven optimization.
• Coach analysts and teams on best practices in Azure, Power BI, and manufacturing analytics.

 Technical Competencies

• Advanced experience with Azure Analytics technologies:
  • Azure Synapse Analytics
  • Azure Data Factory
  • Azure Data Lake Storage (ADLS Gen2)
  • Azure SQL / SQL Server
  • Microsoft Fabric (highly desirable)
• Expert-level skills in Power BI, including advanced DAX and enterprise semantic      models.
• Strong SQL (T-SQL) querying and optimization skills.
• Experience analyzing manufacturing datasets such as:
  • MES/SCADA data
  • Machine telemetry / IIoT signals
  • ERP (e.g., Dynamics 365, SAP) production and inventory data
  • Quality, scrap, and process control data
• Familiarity with statistical modelling, predictive analytics, and Python/R is      advantageous.

Manufacturing Domain Knowledge

• 5+ years in data analytics, with at least 2+ years supporting manufacturing or industrial operations.
• Understanding of lean manufacturing principles, Six Sigma, SPC, and continuous improvement methodologies.
• Experience supporting operational KPIs, maintenance analytics, and real-time monitoring use cases.

Preferred Qualifications

• Microsoft certifications such as PL-300, DP-203, DP-500.
• Experience with Azure IoT Hub, Azure Digital Twins, or similar IIoT platforms.
• Exposure to predictive maintenance or ML models in Azure ML or Fabric ML.
• Background in industrial engineering, production systems, or related fields.