Join a team recognized for leadership, innovation and diversity
The future is what you make it.
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.
LOCATION: Atlanta, GA
Are you ready to help make the future with us?
You will have the opportunity to work on challenging projects, leverage the latest AI technologies, and make a significant impact on optimizing operations and driving growth for our customers. The role offers professional growth, collaboration with experts, and the chance to be at the forefront of AI-driven industrial solutions.
BENEFITS:
Benefits provided may differ by role and location. Learn more at benefits.honeywell.com.
* 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
KEY RESPONSIBILITIES:
Data Engineering & AI Pipeline Development:
* 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
DataOps:
* 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
Collaboration & Innovation:
* 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
*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
WE VALUE:
*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
Additional Information
- JOB ID: req483542
- Category: Engineering
- Location: 715 Peachtree Street, N.E.,Atlanta,Georgia,30308,United States
- Exempt
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
