Honeywell

1 month ago

Lead Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Lead the design and delivery of enterprise-grade data pipelines and AI-ready data products for Honeywell’s Industrial AI & Data Platforms. Architect medallion lakehouse architectures, real-time streaming pipelines, and GenAI-ready data workflows; mentor engineers; partner with data science and product teams to drive scalable, secure data solutions across global industrial operations.

Location: Atlanta

Workplace: Hybrid

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Architect end-to-end data pipelines processing terabytes of IoT telemetry on Azure Databricks (PySpark DLT, Lakeflow) using medallion Lakehouse architecture.
•Design and optimize real-time ingestion pipelines from Azure Event Hub and Apache Kafka for high-volume industrial IoT telemetry.
•Build fault-tolerant, idempotent streaming architectures handling schema evolution, backpressure, and latency SLAs.
•Lead architecture reviews, set engineering standards, and drive decisions on data modeling, pipeline design, and platform evolution.
•Define technical direction for AI-ready data products including vector stores, embedding pipelines, and RAG-ready structured/unstructured data.

Pay and Benefits

Perks:Health InsuranceDentalVision401kParential LeaveLife InsurancePaid LeaveRemote Work

Key Requirements

•8+ years of data engineering experience with at least 2 years in a lead or senior role
•Hands-on experience building and operating medallion lakehouse architectures (Bronze / Silver / Gold)
•Deep expertise in Apache Spark / PySpark with production experience on Azure Databricks at scale
•Strong proficiency with streaming platforms - Apache Kafka and/or Azure Event Hub for real-time IoT data
•Cloud data architecture skills (Azure preferred; AWS/GCP a plus) with experience designing scalable, cost-effective data lakes and warehouses using cloud-native services

Experience:8+ yearsIoTCloudGenAIAIData engineering

Skills:PySparkApache SparkAzure DatabricksKafkaAzure Event HubCloud data architecturesData lakeData warehouseData modelingML/GenAI pipelinesMLOpsGitHub Actions

Languages:EnglishUS English

Tech Stack:PythonPySparkApache SparkAzure DatabricksKafkaAzure Event HubAzureSpark StreamingKubernetesDockerGitHub Actions

Company Brief

Honeywell

Global diversified technology and manufacturing company providing aerospace systems, building technologies, performance materials, and safety & productivity solutions for industrial, commercial, and consumer markets.

Industry: Conglomerates & Holding Companies

Company Size: Enterprise (1,001+ employees)

Revenue: USD 25B to 50B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Charlotte, United States

Founded: 1906

Glassdoor: 3.8

Website LinkedIn Glassdoor

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Honeywell

1 month ago

Lead Data Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 6 hours agoStatus: Live

Job Summary

Location: Atlanta

Workplace: Hybrid

Employment Type: Full time

Job Function: Administration & Executive Assistance

Key Responsibilities

•Architect end-to-end data pipelines processing terabytes of IoT telemetry on Azure Databricks (PySpark DLT, Lakeflow) using medallion Lakehouse architecture.
•Design and optimize real-time ingestion pipelines from Azure Event Hub and Apache Kafka for high-volume industrial IoT telemetry.
•Build fault-tolerant, idempotent streaming architectures handling schema evolution, backpressure, and latency SLAs.
•Lead architecture reviews, set engineering standards, and drive decisions on data modeling, pipeline design, and platform evolution.
•Define technical direction for AI-ready data products including vector stores, embedding pipelines, and RAG-ready structured/unstructured data.

Pay and Benefits

Perks:Health InsuranceDentalVision401kParential LeaveLife InsurancePaid LeaveRemote Work

Key Requirements

•8+ years of data engineering experience with at least 2 years in a lead or senior role
•Hands-on experience building and operating medallion lakehouse architectures (Bronze / Silver / Gold)
•Deep expertise in Apache Spark / PySpark with production experience on Azure Databricks at scale
•Strong proficiency with streaming platforms - Apache Kafka and/or Azure Event Hub for real-time IoT data
•Cloud data architecture skills (Azure preferred; AWS/GCP a plus) with experience designing scalable, cost-effective data lakes and warehouses using cloud-native services

Experience:8+ yearsIoTCloudGenAIAIData engineering

Skills:PySparkApache SparkAzure DatabricksKafkaAzure Event HubCloud data architecturesData lakeData warehouseData modelingML/GenAI pipelinesMLOpsGitHub Actions

Languages:EnglishUS English

Tech Stack:PythonPySparkApache SparkAzure DatabricksKafkaAzure Event HubAzureSpark StreamingKubernetesDockerGitHub Actions

Company Brief

Honeywell

Industry: Conglomerates & Holding Companies

Company Size: Enterprise (1,001+ employees)

Revenue: USD 25B to 50B

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Charlotte, United States

Founded: 1906

Glassdoor: 3.8

Website LinkedIn Glassdoor