Applied Materials

2 months ago

Process Intelligence Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Design, build, and maintain industrial and systems engineering data modeling and analytics solutions that improve decision-making across logistics, supply chain, and manufacturing. Partner with engineering and operations stakeholders to translate business questions into reporting specifications, KPI frameworks, dashboards, and actionable insights. Develop ETL pipelines and automated dataset refresh workflows using tools like Power BI/Tableau, SQL, Python, and big-data/cloud platforms.

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Mid level

Key Responsibilities

•Design and develop reporting solutions and KPI frameworks for logistics, supply chain, and manufacturing teams.
•Build and maintain dashboards, analytical data models, and automated workflows for dataset refresh reliability.
•Develop scalable ETL pipelines for ingestion, cleansing, integration, and transformation of large datasets across SAP, Databricks, SQL data warehouses, and operational systems.
•Perform ad-hoc statistical, diagnostic, and root-cause analysis using SQL and Python to support business investigations and operational improvements.
•Apply statistical and scenario-based simulation (e.g., what-if, Monte Carlo, sensitivity analysis) to evaluate outcomes and communicate results through dashboards and narratives.

Key Requirements

•Bachelor’s degree required; Master’s preferred in Industrial & Systems Engineering, Computer Science, Business Analytics, Systems Engineering, or a related field.
•4–7 years of experience in process intelligence, analytics, dashboarding, or data-engineering–adjacent environments.
•Strong proficiency in SQL and Python for analytics, problem-solving, and investigation support.
•Expertise with Power BI, Tableau, or equivalent visualization tools and KPI/dashboard development.
•Experience designing ETL/ELT data pipelines and data modeling (e.g., star/snowflake schemas) across enterprise systems and data warehouses.

Experience:4-7 yearsAnalyticsData engineeringLogisticsSupply chainManufacturingData visualization

Education:Bachelor's in Industrial & Systems Engineering, Computer Science, Business Analytics, Systems Engineering or a related field

Skills:CommunicationStakeholder managementCollaborationAnalytical mindsetContinuous improvement

Tech Stack:Power BITableauSQLPythonETLELTSAPDatabricksDAXAzureSnowflakeAWSGCPData modelingStar/snowflake schemasMonte Carlo simulationScenario simulationDashboardsKPI frameworksData refresh pipelines

Company Brief

Applied Materials

Provides semiconductor manufacturing equipment, services, and software used to build advanced chips and display technologies. Its tools support materials engineering, deposition, etching, inspection, and process control for major electronics manufacturers worldwide.

Industry: Industrial Machinery

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1967

Glassdoor: 3.9

Website LinkedIn Glassdoor

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Applied Materials

2 months ago

Process Intelligence Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 5 hours agoStatus: Live

Job Summary

Location: Singapore

Workplace: Onsite

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Mid level

Key Responsibilities

•Design and develop reporting solutions and KPI frameworks for logistics, supply chain, and manufacturing teams.
•Build and maintain dashboards, analytical data models, and automated workflows for dataset refresh reliability.
•Develop scalable ETL pipelines for ingestion, cleansing, integration, and transformation of large datasets across SAP, Databricks, SQL data warehouses, and operational systems.
•Perform ad-hoc statistical, diagnostic, and root-cause analysis using SQL and Python to support business investigations and operational improvements.
•Apply statistical and scenario-based simulation (e.g., what-if, Monte Carlo, sensitivity analysis) to evaluate outcomes and communicate results through dashboards and narratives.

Key Requirements

•Bachelor’s degree required; Master’s preferred in Industrial & Systems Engineering, Computer Science, Business Analytics, Systems Engineering, or a related field.
•4–7 years of experience in process intelligence, analytics, dashboarding, or data-engineering–adjacent environments.
•Strong proficiency in SQL and Python for analytics, problem-solving, and investigation support.
•Expertise with Power BI, Tableau, or equivalent visualization tools and KPI/dashboard development.
•Experience designing ETL/ELT data pipelines and data modeling (e.g., star/snowflake schemas) across enterprise systems and data warehouses.

Experience:4-7 yearsAnalyticsData engineeringLogisticsSupply chainManufacturingData visualization

Education:Bachelor's in Industrial & Systems Engineering, Computer Science, Business Analytics, Systems Engineering or a related field

Skills:CommunicationStakeholder managementCollaborationAnalytical mindsetContinuous improvement

Tech Stack:Power BITableauSQLPythonETLELTSAPDatabricksDAXAzureSnowflakeAWSGCPData modelingStar/snowflake schemasMonte Carlo simulationScenario simulationDashboardsKPI frameworksData refresh pipelines

Company Brief

Applied Materials

Industry: Industrial Machinery

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1967

Glassdoor: 3.9

Website LinkedIn Glassdoor