Lead Data Engineer

Honeywell
Atlanta
Workplace: HybridFull timeFunction: Administration & Executive AssistanceExperience: 8+ yearsSkills: ["PySpark","Apache Spark","Azure Databricks","Kafka","Azure Event Hub","Cloud data architectures","Data lake","Data warehouse","Data modeling","ML/GenAI pipelines","MLOps","GitHub Actions"]

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.

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FursaFursa
Honeywell
Honeywell
4 months ago

Lead Data Engineer

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Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live
Reposted: similar role first listed 6 months ago

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
Glassdoor: 3.8
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