IT Analyst II Databs/Storg

ZF Group; Gray Court (SC); On-site; USD 85,000 - 115,000; Full time

Job summary

ZF Group is seeking a Smart Factory Data Analyst to design and maintain data-driven BI solutions for manufacturing performance. You will build dashboards, data models, and analytical tools using SQL, Power BI, and Python across MES, ERP, and other data sources.

The role emphasizes data quality, governance, and actionable insights to improve uptime, quality, and cost metrics. Ideal candidates bring 3+ years in data analytics within manufacturing IT or digitalization contexts, strong SQL/Power

Qualifications

• Bachelor’s degree in IT, Data Analytics, Computer Science, Business Intelligence, Engineering, Industrial Engineering, or related field. 3+ years of relevant professional experience.
• 3+ years of experience in data analytics, business intelligence, Manufacturing IT, Smart Factory, digitalization, or similar analytical roles.
• Hands-on experience with SQL, Microsoft Power BI, and Python for data extraction, transformation, modeling, validation, reporting, automation, and analysis.
• Strong understanding of relational data, joins, keys, data types, transformation logic, and data-quality principles including accuracy, consistency, reconciliation, and traceability.
• Ability to translate manufacturing and business requirements into data models, dashboards, KPIs, visualizations, and decision-support solutions.
• Experience analyzing manufacturing data and KPIs such as OEE, downtime, cycle time, scrap, quality, productivity, and cost performance.
• Experience with enterprise data platforms and manufacturing systems such as SQL Server, Azure SQL, Databricks, Snowflake, SAP, MES, APIs, and ETL/ELT pipelines; advanced Power BI/DAX/Power Query knowledge preferred.
• Nice to have: Knowledge of project management, data governance, Power Platform, industrial data integration, Lean/Continuous Improvement, IATF 16949 and effective collaboration with Production, Engineering, Quality, Maintenance, Controlling, and IT teams.

Responsibilities

• Design, develop, and maintain BI solutions, dashboards, reports, data models, and analytical tools for manufacturing and support functions using SQL, Power BI, Python, and related technologies.
• Extract, combine, transform, and analyze data from MES, ERP, quality, maintenance, databases, APIs, files, connected equipment, and other sources.
• Define and implement data-validation, reconciliation, and quality controls to ensure data completeness, consistency, accuracy, freshness, and traceability.
• Translate operational and business requirements into data specifications, KPI definitions, visualizations, and actionable insights covering production performance, quality, downtime, productivity, and cost drivers.
• Document data sources, transformation logic, KPI definitions, assumptions, and access concepts while applying data-governance and security requirements.
• Coordinate testing, user acceptance, deployment, training, and ongoing performance monitoring for new or enhanced data products.
• Apply basic project-management methods to define scope, milestones, and priorities; contribute to smaller analytics and digitalization initiatives.
• Communicate findings and recommendations to technical and non-technical stakeholders and identify opportunities to standardize and replicate successful solutions across production environments.

Skills

SQL

Power BI

Python

Data analytics

Manufacturing IT

Education

Bachelor’s degree in IT/Data Analytics/CS/BI/Engineering

Tools

SQL Server

Azure SQL

Databricks

Snowflake

MES

SAP

Job description

The Smart Factory Data Analyst develops and maintains data-driven solutions that improve manufacturing performance and support Smart Factory and Industry 4.0 initiatives.

What you can look forward to as Smart Factory Data Analyst :

• Design, develop, and maintain business-intelligence solutions, dashboards, reports, data models, and analytical tools for manufacturing and support functions using SQL, Microsoft Power BI, Python, and related technologies.
• Extract, combine, transform, and analyze data from MES, ERP, quality, maintenance, databases, APIs, files, connected equipment, and other relevant sources.
• Define and implement data-validation, reconciliation, and quality controls to ensure data completeness, consistency, accuracy, freshness, and traceability; investigate discrepancies and coordinate corrective actions with process owners and IT.
• Translate operational and business requirements into data specifications, KPI definitions, visualizations, and actionable insights covering production performance, quality, downtime, productivity, and cost drivers.
• Document data sources, transformation logic, KPI definitions, assumptions, access concepts, and user instructions while applying applicable data-governance, cybersecurity, Production IT Security, and quality-management requirements.
• Coordinate testing, user acceptance, deployment, training, operational handover, and ongoing performance monitoring for new or enhanced data products.
• Apply basic project-management methods to define scope, deliverables, milestones, responsibilities, risks, priorities, and status; coordinate smaller analytics and digitalization initiatives and contribute work packages to larger programs.
• Communicate findings and recommendations to technical and non-technical stakeholders and identify opportunities to standardize and replicate successful solutions across comparable production environments /Contribute to the plant Smart Factory and data analytics roadmap and perform other duties as assigned.

Your Profile asSmart Factory Data Analyst:

• Bachelor’s degree in IT, Data Analytics, Computer Science, Business Intelligence, Engineering, Industrial Engineering, or related field, with 3+ years of relevant professional experience.
• 3+ years of experience in data analytics, business intelligence, Manufacturing IT, Smart Factory, digitalization, or similar analytical roles.
• Hands-on experience with SQL, Microsoft Power BI, and Python for data extraction, transformation, modeling, validation, reporting, automation, and analysis.
• Strong understanding of relational data, joins, keys, data types, transformation logic, and data-quality principles including accuracy, consistency, reconciliation, and traceability.
• Ability to translate manufacturing and business requirements into data models, dashboards, KPIs, visualizations, and decision-support solutions.
• Experience analyzing manufacturing data and KPIs such as OEE, downtime, cycle time, scrap, quality, productivity, and cost performance.
• Experience with enterprise data platforms and manufacturing systems such as SQL Server, Azure SQL, Databricks, Snowflake, SAP, MES, APIs, and ETL/ELT pipelines; advanced Power BI/DAX/Power Query knowledge preferred.
• Nice to have: Knowledge of project management, data governance, Power Platform, industrial data integration, Lean/Continuous Improvement, IATF 16949 and effective collaboration with Production, Engineering, Quality, Maintenance, Controlling, and IT teams.