Sr Advanced Data Engineer
Honeywell
Sr Advanced Data Engineer
Job Description
Sr Advanced Data Engineer
Location: Atlanta, GA (Hybrid)
Overview
Join Honeywell's high-performing global team as a Sr Advanced Data Engineer and drive the future of industrial AI/ML solutions. You will architect and implement scalable data pipelines that power cutting-edge products for Honeywell's Industrial customers, with a focus on IoT, real-time data processing, Large Language Models (LLMs), autonomous agents, and real-time inference systems. Reporting directly to our Sr Data Engineering Manager, you'll work in a hybrid environment from our state-of-the-art Atlanta, GA facility, collaborating with cross-functional teams to deliver transformative AI data products that enhance operational efficiency and innovation across industries.
Key Responsibilities
- Design, build, and optimize scalable data pipelines for ingesting, processing, and transforming high-volume IoT and real-time streaming data from industrial sensors and edge devices.
- Architect end-to-end data infrastructure supporting AI/ML workloads, including integration with LLMs, vector databases, and real-time inference engines.
- Lead the development of robust ETL/ELT processes using cloud-native tools to ensure data quality, reliability, and low-latency performance.
- Collaborate with data scientists, ML engineers, and product teams to productionize AI models and enable advanced analytics for industrial applications.
- Implement monitoring, alerting, and automation for data pipelines to maintain high availability and scalability in production environments.
- Mentor junior engineers and drive best practices in data engineering, contributing to team knowledge sharing and technical roadmaps.
What Makes This Role Exciting
This role offers the chance to work on groundbreaking AI initiatives at a Fortune 100 company, impacting real-world industrial operations with technologies like LLMs and autonomous systems. Enjoy hybrid flexibility, cutting-edge tools, global collaboration, and opportunities for career growth in a supportive, innovative culture. Be part of shaping Honeywell's leadership in Industrial IoT and AI.
Summary
As a Senior Advanced Data Engineer here at Honeywell, you 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 report directly to our Sr Data Engineering Manager, and you’ll work out of our Atlanta, GA location on a Hybrid work schedule.
Locations
- 715 Peachtree Street, N.E., , Peachtree City, GA, US 30308
Salary
60,000 - 120,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Expertise in Python, Scala, or Java for data pipeline developmentintermediate
- Proficiency in Apache Kafka, Spark, Flink for streaming and batch processingintermediate
- Experience with cloud data services (e.g., AWS Glue, EMR, S3; Azure Synapse, Databricks)intermediate
- Knowledge of SQL, NoSQL databases, and vector databases (e.g., Pinecone, Weaviate)intermediate
- Strong understanding of containerization (Docker, Kubernetes) and orchestration toolsintermediate
- Familiarity with ML frameworks (TensorFlow, PyTorch) and LLM integration (LangChain, LlamaIndex)intermediate
- Excellent problem-solving and analytical skillsintermediate
- Strong communication and collaboration abilities in agile teamsintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (experience)
- 7+ years of experience in data engineering, with proven expertise in building scalable data pipelines for AI/ML applications (experience)
- Strong experience with real-time data processing and IoT data streams in industrial or enterprise environments (experience)
- Proficiency in cloud platforms (AWS, Azure, or GCP) and distributed data processing frameworks (experience)
- Hands-on experience with LLMs, vector databases, or real-time inference systems (experience)
- Demonstrated ability to lead complex data projects from design to production deployment (experience)
Preferred Qualifications
- Master's degree in Computer Science, Data Engineering, or related field (experience)
- Certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, or Databricks Certified Data Engineer (experience)
- Experience with industrial IoT protocols (e.g., MQTT, OPC UA) and edge computing (experience)
Responsibilities
- Design and develop scalable data pipelines for processing petabyte-scale IoT and real-time data using tools like Apache Kafka, Spark Streaming, and Flink
- Architect data infrastructure integrating LLMs, autonomous agents, and real-time inference systems with platforms like Kubernetes and Ray
- Implement data governance, quality controls, and observability using tools like Great Expectations, Monte Carlo, or Prometheus
- Optimize data storage solutions with Snowflake, Delta Lake, or vector stores like Pinecone for AI workloads
- Collaborate with cross-functional teams to define data requirements and deploy ML models into production environments
- Lead troubleshooting and performance tuning of data systems to ensure 99.9% uptime and sub-second latency
- Contribute to technical roadmaps and mentor team members on advanced data engineering practices
Benefits
- general: Competitive base salary and performance-based bonuses
- general: Comprehensive health, dental, and vision insurance with low premiums
- general: 401(k) retirement plan with generous company matching
- general: Professional development programs, tuition reimbursement, and certification support
- general: Flexible hybrid work schedule with 4-5 weeks PTO annually
- general: Employee stock purchase plan and wellness incentives
Tags & Categories
Answer 10 quick questions to check your fit for Sr Advanced Data Engineer @ Honeywell.
Related Books and Jobs
Sr Advanced Data Engineer
Honeywell
Sr Advanced Data Engineer
Job Description
Sr Advanced Data Engineer
Location: Atlanta, GA (Hybrid)
Overview
Join Honeywell's high-performing global team as a Sr Advanced Data Engineer and drive the future of industrial AI/ML solutions. You will architect and implement scalable data pipelines that power cutting-edge products for Honeywell's Industrial customers, with a focus on IoT, real-time data processing, Large Language Models (LLMs), autonomous agents, and real-time inference systems. Reporting directly to our Sr Data Engineering Manager, you'll work in a hybrid environment from our state-of-the-art Atlanta, GA facility, collaborating with cross-functional teams to deliver transformative AI data products that enhance operational efficiency and innovation across industries.
Key Responsibilities
- Design, build, and optimize scalable data pipelines for ingesting, processing, and transforming high-volume IoT and real-time streaming data from industrial sensors and edge devices.
- Architect end-to-end data infrastructure supporting AI/ML workloads, including integration with LLMs, vector databases, and real-time inference engines.
- Lead the development of robust ETL/ELT processes using cloud-native tools to ensure data quality, reliability, and low-latency performance.
- Collaborate with data scientists, ML engineers, and product teams to productionize AI models and enable advanced analytics for industrial applications.
- Implement monitoring, alerting, and automation for data pipelines to maintain high availability and scalability in production environments.
- Mentor junior engineers and drive best practices in data engineering, contributing to team knowledge sharing and technical roadmaps.
What Makes This Role Exciting
This role offers the chance to work on groundbreaking AI initiatives at a Fortune 100 company, impacting real-world industrial operations with technologies like LLMs and autonomous systems. Enjoy hybrid flexibility, cutting-edge tools, global collaboration, and opportunities for career growth in a supportive, innovative culture. Be part of shaping Honeywell's leadership in Industrial IoT and AI.
Summary
As a Senior Advanced Data Engineer here at Honeywell, you 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 report directly to our Sr Data Engineering Manager, and you’ll work out of our Atlanta, GA location on a Hybrid work schedule.
Locations
- 715 Peachtree Street, N.E., , Peachtree City, GA, US 30308
Salary
60,000 - 120,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Expertise in Python, Scala, or Java for data pipeline developmentintermediate
- Proficiency in Apache Kafka, Spark, Flink for streaming and batch processingintermediate
- Experience with cloud data services (e.g., AWS Glue, EMR, S3; Azure Synapse, Databricks)intermediate
- Knowledge of SQL, NoSQL databases, and vector databases (e.g., Pinecone, Weaviate)intermediate
- Strong understanding of containerization (Docker, Kubernetes) and orchestration toolsintermediate
- Familiarity with ML frameworks (TensorFlow, PyTorch) and LLM integration (LangChain, LlamaIndex)intermediate
- Excellent problem-solving and analytical skillsintermediate
- Strong communication and collaboration abilities in agile teamsintermediate
Required Qualifications
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related technical field (experience)
- 7+ years of experience in data engineering, with proven expertise in building scalable data pipelines for AI/ML applications (experience)
- Strong experience with real-time data processing and IoT data streams in industrial or enterprise environments (experience)
- Proficiency in cloud platforms (AWS, Azure, or GCP) and distributed data processing frameworks (experience)
- Hands-on experience with LLMs, vector databases, or real-time inference systems (experience)
- Demonstrated ability to lead complex data projects from design to production deployment (experience)
Preferred Qualifications
- Master's degree in Computer Science, Data Engineering, or related field (experience)
- Certifications such as AWS Certified Data Analytics, Google Professional Data Engineer, or Databricks Certified Data Engineer (experience)
- Experience with industrial IoT protocols (e.g., MQTT, OPC UA) and edge computing (experience)
Responsibilities
- Design and develop scalable data pipelines for processing petabyte-scale IoT and real-time data using tools like Apache Kafka, Spark Streaming, and Flink
- Architect data infrastructure integrating LLMs, autonomous agents, and real-time inference systems with platforms like Kubernetes and Ray
- Implement data governance, quality controls, and observability using tools like Great Expectations, Monte Carlo, or Prometheus
- Optimize data storage solutions with Snowflake, Delta Lake, or vector stores like Pinecone for AI workloads
- Collaborate with cross-functional teams to define data requirements and deploy ML models into production environments
- Lead troubleshooting and performance tuning of data systems to ensure 99.9% uptime and sub-second latency
- Contribute to technical roadmaps and mentor team members on advanced data engineering practices
Benefits
- general: Competitive base salary and performance-based bonuses
- general: Comprehensive health, dental, and vision insurance with low premiums
- general: 401(k) retirement plan with generous company matching
- general: Professional development programs, tuition reimbursement, and certification support
- general: Flexible hybrid work schedule with 4-5 weeks PTO annually
- general: Employee stock purchase plan and wellness incentives
Tags & Categories
Answer 10 quick questions to check your fit for Sr Advanced Data Engineer @ Honeywell.
Related Books and Jobs