Lead Data & AI Engineer

The Data & AI Platform Engineer at Sabert Corporation is a hybrid role that plays a strategic and hands-on role at the intersection of data engineering, advanced analytics, and artificial intelligence. This position is responsible for designing, building, and optimizing scalable data platforms and AI-driven solutions that support enterprise-wide decision-making, advancing Sabert’s digital transformation by integrating data across manufacturing, supply chain, finance, sales, HR, and customer service functions.

Responsibilities

• Design, develop, and maintain scalable, reliable data pipelines integrating structured and unstructured data from systems such as SAP S/4HANA, MES, SCADA, CRM, and other enterprise platforms.
• Build and manage modern enterprise data environments, including Microsoft Fabric, Azure-based lakehouse architectures, and ETL/ELT pipelines.
• Ensure high-quality, governed, and trusted data through implementation of data quality frameworks, validation processes, and consistency checks.
• Establish and maintain master data management (MDM) practices and enforce enterprise data governance standards.
• Enable real-time and near real-time data ingestion and processing from manufacturing systems, industrial IoT devices, and operational technology (OT) environments.
• Develop, validate, and deploy advanced analytics and machine learning models, including demand forecasting, predictive maintenance, supply chain optimization, and financial planning models.
• Build and operationalize end-to-end machine learning pipelines supporting anomaly detection, process optimization, and performance improvement.
• Collaborate with cross-functional business partners to translate complex business challenges into scalable analytical solutions and production-ready AI models.
• Perform exploratory data analysis to identify patterns, trends, and insights that drive continuous improvement across operations.
• Design, develop, and deploy AI-powered solutions such as conversational agents, copilots, and workflow automation tools to enhance productivity.
• Leverage modern AI frameworks, including large language models (LLMs) and agent-based architectures, to accelerate innovation across business functions.
• Establish reusable AI solution patterns, documentation, best practices, and governance guardrails for responsible AI adoption.
• Monitor, evaluate, and continuously improve deployed analytics and AI solutions based on performance metrics and stakeholder feedback.
• Serve as a key liaison between IT and OT teams, ensuring alignment of data solutions with plant operations and enterprise priorities.
• Define and enforce enterprise data security, governance, and compliance standards in alignment with regulatory and company requirements.
• Document data architectures, pipelines, models, and solutions to support knowledge sharing, scalability, and maintainability.
• Work in accordance with all Sabert Corporation policies and procedures, including those related to safety, quality, food/product safety, environmental responsibility, data security, and regulatory compliance.

Requirements

• Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Information Systems, or a related field.
• Minimum of 5+ years of experience in data engineering, data science, advanced analytics, or related roles.
• Proven experience building and managing cloud-based data platforms and analytics solutions within enterprise environments.
• Experience working with ERP, MES, CRM, or similar enterprise systems, preferably within a manufacturing or CPG organization.

Skills

• Strong expertise in data engineering, data modeling, database design, and modern data architectures (lakehouse, data warehousing, ETL/ELT).
• Proficiency in Python and SQL for data analysis, pipeline development, and machine learning model creation.
• Experience with cloud platforms such as Microsoft Azure, Microsoft Fabric, Databricks, or Snowflake, and integration with SAP ecosystems.
• Strong experience with data visualization and business intelligence tools, including Power BI and semantic data modeling.
• Hands-on experience with machine learning techniques, including regression, classification, clustering, and time-series forecasting.
• Proven ability to deploy predictive models and analytics solutions into production environments.
• Familiarity with AI/ML frameworks, large language models (LLMs), and modern AI application development.
• Understanding of MLOps practices, including model lifecycle management, deployment, monitoring, and version control.
• Experience working with industrial IoT, SCADA, and MES systems, including real-time data processing.
• Knowledge of manufacturing, supply chain, or CPG data environments, with an understanding of OT/IT integration challenges.
• Strong analytical thinking, problem-solving skills, and focus on delivering measurable business impact.
• Excellent communication and stakeholder engagement skills, with the ability to manage multiple priorities in a dynamic environment.

Benefits

• Competitive compensation and a generous benefits package.
• Full health insurance (medical, dental, and vision).
• 401(k) retirement plan.
• Life insurance and disability coverage.