IoT Data Engineer: Real-Time AI & Pipelines Lead

Honeywell International, Inc.; Atlanta (GA); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

401(k) Match

Paid Holidays

Job summary

Honeywell International, Inc. is seeking a Senior Data Engineer to join a global team delivering AI and data solutions for industrial customers. The role focuses on IoT and real-time data processing, designing scalable data architectures and pipelines to enable next-generation AI capabilities and real-time analytics.

The position reports to the Data Engineering Manager and is based in Atlanta, GA on a Hybrid schedule. For the first 90 days, new hires must be onsite five days a week.

Qualifications

• Minimum 5 years of production data pipeline experience with Databricks.
• Experience implementing medallion architecture (Bronze/Silver/Gold) with Delta Lake and Delta Live Tables.
• Proficient in PySpark for distributed processing.
• Cloud experience on Azure and/or GCP; Databricks familiarity.
• CI/CD practices using GitHub Actions; DataOps practices including data quality testing.

Responsibilities

• Design scalable data architectures for high-volume IoT telemetry and AI workloads.
• Build and maintain AI data pipelines (training data, feature engineering, inference data).
• Develop RAG systems with vector databases and embedding pipelines.
• Lead Databricks-based data platforms and support GenAI integrations.
• Collaborate with ML engineering and data science teams; ensure governance and observability.

Skills

Databricks

PySpark

Azure

GCP

Kafka

GitHub Actions

DataOps

LangChain

Tools

Delta Lake

DLT

LangChain

LangGraph

Job description

Honeywell International, Inc. is seeking a Senior Data Engineer to join a global team delivering AI and data solutions for industrial customers. The role focuses on IoT and real-time data processing, designing scalable data architectures and pipelines to enable next-generation AI capabilities and real-time analytics.

The position reports to the Data Engineering Manager and is based in Atlanta, GA on a Hybrid schedule. For the first 90 days, new hires must be onsite five days a week.