Data Engineer I - AI & Industrial IoT Solutions

Honeywell International • Atlanta, GA

246d

About The Position

Honeywell is seeking a Senior Data Engineer to join our dynamic global team in delivering cutting-edge AI/ML data products for industrial customers. In this role, you will design and implement scalable data pipelines, enabling next-generation AI solutions such as Large Language Models (LLMs), autonomous agents, and real-time inference systems. With a strong focus on IoT and real-time data processing, you will work at the intersection of industrial telemetry data and modern AI technologies to develop innovative, high-impact solutions. Join us in shaping the future of industrial AI.

Requirements

• Bachelor's degree from an accredited institution in a technical discipline such as science, technology, engineering or mathematics
• 4+ years of data engineering experience with strong understanding of CDC, ELT/ETL workflows, streaming replication, and data quality frameworks
• 2+ years of hands-on experience with PySpark/Scala
• 2+ years of experience with cloud platforms (Azure/GCP/Databricks), particularly in implementing AI/ML data workflows

Nice To Haves

• Strong understanding of data modeling for both analytical and AI workloads
• Experience implementing RAG architectures and working with LLM-powered applications
• Expertise in real-time data processing frameworks (Apache Spark Streaming, Structured Streaming)
• Knowledge of MLOps practices and experience building data pipelines for AI model deployment
• Experience with time-series databases and IoT data modeling patterns
• Familiarity with containerization (Docker) and orchestration (Kubernetes) for AI workloads
• Strong background in data quality implementation for AI training data
• Experience with graph databases and knowledge graphs for AI applications
• Experience working with distributed teams and cross-functional collaboration
• Knowledge of data security and governance practices for AI systems
• Expertise in version control systems, CI/CD methodologies
• Experience working on analytics projects with Agile and Scrum Methodologies

Responsibilities

• Design and implement scalable data architectures to process high-volume IoT sensor data and telemetry streams, ensuring reliable data capture and processing for AI/ML workloads
• Build and maintain data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows
• Develop and optimize RAG (Retrieval Augmented Generation) systems, including vector databases, embedding pipelines, and efficient retrieval mechanisms
• Create robust data integration solutions that combine industrial IoT data streams with enterprise data sources for AI model training and inference
• Implement DataOps practices to ensure continuous integration and delivery of data pipelines powering AI solutions
• Design and maintain automated testing frameworks for data quality, data drift detection, and AI model performance monitoring
• Create self-service data assets enabling data scientists and ML engineers to access and utilize data efficiently
• Design and maintain automated documentation systems for data lineage and AI model provenance
• Partner with ML engineers and data scientists to implement efficient data workflows for model training, fine-tuning, and deployment
• Drive continuous improvement in data engineering practices and tooling
• Establish best practices for data pipeline development and maintenance in AI contexts
• Drive projects to completion while working in an agile environment with evolving requirements in the rapidly changing AI landscape

Benefits

• Unlimited Vacation Plan with No Preset Maximums
• Flexible Hybrid Work Schedule
• Medical/Rx Health Savings Account (HSA)
• Dental/Vision
• Short/Long-Term Disability
• Employee Assistance Program (EAP)
• 401(k) Plan
• Education Assistance

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Computer and Electronic Product Manufacturing
• Education Level: Bachelor's degree