- Company Name
- Cargill
- Job Title
- Data Engineering - Manufacturing Data
- Job Description
-
**Job Title**
Data Engineering – Manufacturing Data
**Role Summary**
Lead the design, development, and maintenance of end‑to‑end data platforms that enable real‑time analytics in manufacturing. Oversee edge‑to‑cloud data pipelines, data governance, automated reporting, and the continuous improvement of data infrastructure to support operational and strategic decision making.
**Expectations**
- Deliver scalable, secure, and reliable manufacturing data solutions aligned with business KPIs.
- Drive digital transformation initiatives through automation, edge computing, and cloud integration.
- Manage a multidisciplinary engineering team, setting clear objectives, coaching, and ensuring high productivity.
- Build strong relationships with stakeholders to capture data needs and translate them into technical requirements.
**Key Responsibilities**
- Architect and maintain robust data systems for large, complex manufacturing datasets.
- Design and implement data pipelines that ingest, process, and load time‑series and IoT/OT data into cloud environments.
- Define and enforce data models, formats, and governance standards across heterogeneous sources.
- Develop and maintain automated reporting and analytics dashboards for real‑time insights.
- Champion data framework standards, prototype new architectures, and promote best practices.
- Manage, mentor, and grow team members, fostering an inclusive and high‑performance culture.
**Required Skills**
- 6+ years of data engineering experience in industrial or manufacturing settings (10+ years preferred).
- Expertise in time‑series data management, data historians, IoT/OT integration, and edge computing.
- Strong knowledge of cloud platforms (AWS, Azure, GCP) and big‑data technologies (Spark, Flink, Kafka, Hadoop).
- Proven ability to design enterprise‑level data architecture, canonical models, and API‑first interfaces.
- Experience with automation, data orchestration, and digital transformation initiatives.
- Excellent stakeholder management, communication, and leadership skills.
**Required Education & Certifications**
- Bachelor’s degree in Computer Science, Electrical Engineering, Data Engineering, or related field (Master’s degree preferred).
- Relevant certifications such as AWS Certified Big Data – Specialty, Microsoft Certified: Azure Data Engineer Associate, GCP Professional Data Engineer, or equivalent cloud and big‑data credentials.