Innovate to solve the world's most important challenges

The Lead Data Engineer role will be part of a high-performing global team that delivers cutting-edge AI/ML data products for Honeywell's Industrial customers, with a specific focus on IoT and real-time data processing. As a data engineer, you will architect and implement scalable data pipelines that power next-generation AI solutions, including Large Language Models (LLMs), autonomous agents, and real-time inference systems. You will work at the intersection of IoT telemetry data and modern AI technologies to create innovative industrial solutions.

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KEY RESPONSIBILITIES

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Data Engineering & AI Pipeline Development:

\n\nDesign 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\nArchitect and build data pipelines for AI product lifecycle, including training data preparation, feature engineering, and inference data flows\nDevelop and optimize RAG (Retrieval Augmented Generation) systems, including vector databases, embedding pipelines, and efficient retrieval mechanisms\nDesign and implement robust data integration solutions that combine industrial IoT data streams with enterprise data sources for AI model training and inference\n\n

DataOps & Governance:

\n\nDefine a mature DataOps strategies to ensure continuous integration and delivery of data pipelines powering AI solutions\nLead efforts in data quality, observability, and lineage tracking to maintain high integrity in AI/ML datasets.\nCreate self-service data assets enabling data scientists and ML engineers to access and utilize data efficiently\nDesign and maintain automated documentation systems for data lineage and AI model provenance\nEnsure compliance with data governance policies, including security, privacy, and regulatory requirements for AI-driven applications\n\n

Technical Leadership & Innovation:

\n\nLead architectural discussions, establish standards and drive technical excellence across teams\n\n\nPartner with ML engineers and data scientists to implement efficient data workflows for model training, fine-tuning, and deployment\nMentor data engineers on standards, best practices, and innovative approaches to build extensible and reusable solution\nDrive innovation, continuous improvement in data engineering practices and tooling\n\n\nManage stakeholder expectations, aligning data engineering roadmaps with business and AI strategy\n\n

 

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YOU MUST HAVE

\n\nMinimum 8 years of hands-on experience in building data pipelines using large-scale distributed data processing tools, frameworks & platforms (Python, Spark, Databricks)\n6+ years of extensive experience in data management concepts, including data modeling, CDC, ETL/ELT processes, data lakes, and data governance.\n4+ years of hands-on experience with PySpark/Scala\n4+ years of experience with cloud platforms (Azure/GCP/Databricks) particularly in implementing AI/ML solutions\n\n

 

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WE VALUE

\n\nExperience implementing RAG architectures and working with LLM-powered applications\nExpertise in real-time data processing frameworks (Kafka, Apache Spark Streaming, Structured Streaming)\nKnowledge of MLOps practices and experience building data pipelines for AI model deployment\nExperience with time-series databases and IoT data modeling patterns\nFamiliarity with containerization (Docker) and orchestration (Kubernetes) for AI workloads\nStrong background in data quality implementation for AI training data\nExperience with graph databases and knowledge graphs for AI applications\nExperience working with distributed teams and cross-functional collaboration\nKnowledge of data security and governance practices for AI systems\nExpertise in version control systems, CI/CD methodologies\nExperience working on analytics projects with Agile and Scrum Methodologies\nAdditional InformationJOB ID: HRD9085977Category: EngineeringLocation: 715 Peachtree Street, N.E.,Atlanta,Georgia,30308,United StatesExemptGlobal (ALL)

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.