The Data Engineer will be responsible for developing and implementing data-driven solutions and products that optimize operations, enhance efficiency, and drive growth for Honeywell’s Industrial customers. This role focuses on building AI data products using IoT data, handling large-scale streaming and telemetry data, and deploying data pipelines for AI products.

Scope: The role involves collaborating with stakeholders, data scientists, and product teams to create data products that serve analytics solutions and AI/ML needs. It includes implementing data models, data pipelines which integrates diverse data sources, and building analytic solutions leveraging AI

Challenges: The Data Engineer will face challenges such as managing and processing huge volumes of streaming data, ensuring data quality, and implementing efficient solutions while working in a fast-paced environment with ambiguous requirements.

Opportunities: This role offers the opportunity to work on cutting-edge AI projects, leveraging best in class data platforms, develop innovative data products, that transform of industrial operations. Professional Growth opportunity while working alongside a global team of data engineers and ML experts to drive manufacturing innovation and operational excellence.

Joining Honeywell’s data engineering team means being part of a high-performing global team that delivers innovative AI/ML data products for industrial customers. You will have the opportunity to work on challenging projects, leverage the latest AI technologies, and make a significant impact on optimizing operations and driving growth for our customers. The role offers professional growth, collaboration with experts, and the chance to be at the forefront of AI-driven industrial solutions.

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Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

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Joining Honeywell’s data engineering team means being part of a high-performing global team that delivers innovative AI/ML data products for industrial customers. You will have the opportunity to work on challenging projects, leverage the latest AI technologies, and make a significant impact on optimizing operations and driving growth for our customers. The role offers professional growth, collaboration with experts, and the chance to be at the forefront of AI-driven industrial solutions.

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US PERSON REQUIREMENTS:

Due to compliance with US export control laws and regulations, candidate must be a US Person which is defined as a US citizen, US permanent resident, or have protected status In the US under asylum or refugee status or have the ability to obtain an export authorization.

Required Competencies:

• Strong experience in data engineering concepts like CDC, ELT/ETL workflows, streaming replication, and data quality frameworks
• Expertise in data modeling (dimensional, data vault), modern data lake architectures (medallion, delta), and practical experience with schema evolution strategies
• Past experience handling high-volume IoT/telemetry data streams using technologies like Apache Kafka, Azure Event Hubs, or similar.
• Proficiency in programming languages such as Scala or PySpark and Python.
• Experience in building and deploying data pipelines for AI products.
• Familiarity with cloud platforms like Databricks and Azure/GCP

Work Experience:

• 5 years of data engineering experience.
• 2 years of experience in programming with Scala or PySpark.
• 2 years of experience in analyzing and modeling large-scale datasets.

Preferred Competencies:

• Experience with complex SQL queries and large-scale data analytics solutions.
• Knowledge of Agile and Scrum methodologies.
• Expertise in version control systems and CI/CD methodologies.
• Working knowledge of NoSQL/Graph systems and containerization technologies like Docker and Kubernetes.
• Familiarity with GenAI and ML concepts.

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Key Responsibilities

• Lead the design, development, and implementation of data engineering solutions
• Collaborate with cross-functional teams to understand data requirements and deliver solutions
• Design and implement data pipelines and ETL processes
• Ensure the performance, availability, and security of data platforms