Data and Analytics Engineer - Global Manufacturing

Siemens • Wendell, NC

1d • $102,459 - $175,644 • Hybrid

About The Position

Siemens is seeking a Manufacturing Data & Analytics Engineer for its Electrification & Automation Business Unit. The position is based in Wendell, North Carolina, and supports the U.S. manufacturing network by building scalable data pipelines and cloud-based data models for operational reporting, analytics, and continuous improvement. The engineer will collaborate with manufacturing, quality, operational, and Industrial IoT teams to develop trusted data, metrics, dashboards, traceability capabilities, and analytical solutions that help production teams improve performance and make operational decisions.

The role requires a bachelor's degree in a related technical field or equivalent practical experience, at least five years of relevant data solution experience, SQL and programming skills, and hands-on Snowflake experience. Travel to U.S. manufacturing facilities may be required up to 20%. This is a full-time, permanent position with a hybrid work mode.

Requirements

• Bachelor's degree in Data Engineering, Computer Science, Software Engineering, Information Systems, Industrial Engineering, or a related technical field; equivalent practical experience is also considered.
• At least 5 years of experience developing and supporting data pipelines, cloud-based data solutions, or enterprise analytics platforms.
• SQL development skills and proficiency in at least one programming language, such as Python.
• Hands-on experience with Snowflake, including building, maintaining, testing, and troubleshooting data models and transformation pipelines.
• Experience implementing data quality validation, monitoring, testing, and troubleshooting processes.
• Experience translating manufacturing or operational business requirements into metrics, KPIs, and reporting solutions.
• Experience creating operational dashboards, reports, and performance visualizations that support business decision-making.
• Ability and willingness to travel up to 20% to support U.S. manufacturing facilities.
• Legally authorized to work in the United States on a continual and permanent basis without company sponsorship.

Nice To Haves

• At least 5 years of experience in data engineering, manufacturing analytics, Industrial IoT, or industrial digitalization environments.
• Experience with manufacturing, production, time-series, machine, or operational technology data.
• Experience with Kafka, event-driven architectures, or real-time data streaming technologies.
• Knowledge of product traceability solutions and manufacturing genealogy data models.
• Experience integrating edge and cloud-based technologies in manufacturing environments.
• Familiarity with semantic modeling concepts, governed analytics frameworks, and reusable KPI definitions.
• Experience with Grafana, Power BI, Tableau, or other enterprise business intelligence platforms.
• Understanding of data mesh, modern data architectures, or distributed data ownership principles.

Responsibilities

• Build and maintain scalable data pipelines that collect, transform, and deliver manufacturing data for reporting, analytics, and continuous improvement.
• Develop and support cloud-based data models representing production processes, assets, events, and manufacturing performance.
• Collaborate with Industrial IoT and connectivity engineers on data ingestion, validation, monitoring, and troubleshooting across manufacturing systems.
• Define business terms, relationships, and KPI calculations with manufacturing, quality, and operational stakeholders.
• Develop reusable semantic and analytical models to establish consistent reporting standards and trusted operational insights.
• Create dashboards, visualizations, and analytical solutions to help production teams identify losses, monitor performance, and drive improvements.
• Support product traceability initiatives by developing data models and retrieval capabilities for manufacturing visibility and quality investigations.
• Diagnose and resolve data quality, integrity, and performance issues across systems and data sources.
• Document data architectures, schemas, KPI definitions, semantic models, and governance practices.
• Work with business users to turn analytical findings into improvement plans and operational decisions.

Benefits

• Siemens offers a variety of health and wellness benefits; further details are provided through its benefits website.
• Annual pay range of $102,459–$175,644, with a target incentive of 10% of base salary.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level