Manufacturing Data & Analytics Engineer We are looking for a Manufacturing Data & Analytics Engineer. This position will be based in Wendell, NC. You'll make an impact by: - Building and maintaining scalable data pipelines for our US manufacturing network that collect, transform, and deliver manufacturing data for operational reporting, analytics, and continuous improvement initiatives.
- Developing and supporting cloud-based data models that accurately represent production processes, assets, events, and manufacturing performance.
- Collaborating with Industrial IoT and connectivity engineers to ensure reliable data ingestion, validation, monitoring, and troubleshooting across manufacturing systems.
- Defining business terms, relationships, and KPI calculations in partnership with manufacturing, quality, and operational stakeholders.
- Developing reusable semantic and analytical models that establish consistent reporting standards and trusted operational insights.
- Creating dashboards, visualizations, and analytical solutions that help production teams identify losses, monitor performance, and drive measurable improvements.
- Supporting product traceability initiatives by developing data models and retrieval capabilities that improve manufacturing visibility and quality investigations.
- Diagnosing and resolving data quality, integrity, and performance issues across multiple systems and data sources.
- Documenting data architectures, schemas, KPI definitions, semantic models, and governance practices to support long-term scalability and adoption.
- Working closely with business users to translate analytical findings into actionable improvement plans and operational decision-making.
You'll win us over by having the following qualifications: Basic Qualifications: - Bachelor's degree in Data Engineering, Computer Science, Software Engineering, Information Systems, Industrial Engineering, or a related technical field; equivalent practical experience will also be considered.
- 5+ years of experience developing and supporting data pipelines, cloud-based data solutions, or enterprise analytics platforms.
- Experience with SQL development skills and proficiency in at least one programming language such as Python
- Hands-on experience with Snowflake and demonstrated ability to build, maintain, test, and troubleshoot data models and transformation pipelines.
- Experience implementing data quality validation, monitoring, testing, and troubleshooting processes.
- Experience translating manufacturing or operational business requirements into meaningful metrics, KPIs, and reporting solutions.
- Experience creating operational dashboards, reports, and performance visualizations that support business decision-making.
- Willingness and ability 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.
Preferred Qualifications: - 5+ years of experience in data engineering, manufacturing analytics, Industrial IoT, or industrial digitalization environments.
- Experience working 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 within 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.
You'll Benefit FromSiemens offers a variety of health and wellness benefits to our employees. Details regarding our benefits can be found here: https://www.benefitsquickstart.com/siemens/index.html
The pay range for this position is $102,459 - $175,644 annually with a target incentive of 10% of the base salary. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location.
