Sr Advanced Data Engineer

As an Advanced Data Engineer here at Honeywell, you will play a pivotal role in designing, developing, and maintaining our data infrastructure and systems. Your expertise will be crucial in ensuring the efficient handling, processing, and storage of large volumes of data. You will work closely with cross-functional teams to understand data requirements and implement solutions that drive business insights and operational excellence.

In this role, you will impact the organization by developing and optimizing data pipelines, ensuring data quality and integrity, and leveraging advanced data engineering techniques to support data-driven decision-making. Your contributions will enable stakeholders to make informed decisions, improve processes, and drive business growth.

At Honeywell, our people leaders play a critical role in developing and supporting our employees to help them perform at their best and drive change across the company. Help to build a strong, diverse team by recruiting talent, identifying, and developing successors, driving retention and engagement, and fostering an inclusive culture.

• Bachelor’s degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics
• Required experience
• Required trait

• Advanced degree in Computer Science, Data Engineering, or related field
• Experience with big data technologies (e.g., Hadoop, Spark, Kafka)
• Proficiency in programming languages such as Python, Java, or Scala
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)
• Strong problem-solving skills and ability to work in a fast-paced environment

• Design, develop, and implement data engineering solutions to support business needs
• Collaborate with crossfunctional teams to understand data requirements and design data models
• Develop and maintain data pipelines and ETL processes
• Ensure data quality, integrity, and security
• Optimize data storage and retrieval for performance and scalability
• Stay updated on industry best practices and emerging technologies in data engineering