Lead Data Engineer at Honeywell

DescriptionThe Data Engineer will be responsible for developing and implementing data-driven solutions and products that optimize operations enhance efficiency and drive growth for Honeywells 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 AIChallenges: 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 whileworking alongside a global team of data engineers and ML experts to drive manufacturing innovation and operational excellence.Joining Honeywells 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.ResponsibilitiesKey ResponsibilitiesLead the design development and implementation of data engineering solutionsCollaborate with cross-functional teams to understand data requirements and deliver solutionsDesign and implement data pipelines and ETL processesEnsure the performance availability and security of data platformsQualificationsUS 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 frameworksExpertise in data modeling (dimensional data vault) modern data lake architectures (medallion delta) and practical experience with schema evolution strategiesPast 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/GCPWork 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. Key Skills Apache Hive,S3,Hadoop,Redshift,Spark,AWS,Apache Pig,NoSQL,Big Data,Data Warehouse,Kafka,Scala Employment Type : Full-Time Experience: years Vacancy: 1