Hybrid Data Engineer II

at Honeywell

• Job title: Data Engineer II
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: No Education Requirement
• Tech skills: Azure, Cassandra, Cloud, ETL, Hadoop, HBase, HDFS, MongoDB, NoSQL, PySpark, Python, PyTorch, SFDC, Spark, SQL, Tensorflow
• Location requirements: Hybrid, Bengaluru, India

About the role

• Data Engineer II at Honeywell responsible for data architecture, pipelines, and analytics support. Collaborating across teams to ensure data quality and compliance in high-volume environments.

Responsibilities

• Design, implement, and manage the data architecture, systems, and processes to effectively collect, store, process and analyze high volume, high dimensional data
• Create and maintain scalable, efficient, and secure data pipelines, data warehouses, and data lakes
• Ensure consistency in data quality and availability for analysis and reporting including compliance with data governance and security standards
• Work in complex data science and analytics projects in support of the Commercial organization.
• Collaborate with data scientists and analysts to define and structure data for effective analysis and reporting.
• Develop and maintain ETL (Extract, Transform, Load) processes
• Administer, optimize, and manage databases, data warehouses, and data lakes to ensure performance, reliability, and scalability.
• Enforce data governance policies, standards, and best practices to maintain data quality, privacy, and security.
• Create and maintain comprehensive documentation for data architecture, processes, and systems.

Requirements

• 4 + years of relevant experience in Data Engineering, ETL Development, Database Administration.
• Experience in Azure Databricks, CI/CD & Dev Ops Process
• Expert in scripting and querying languages, such as Python, SQL, PySpark
• Experience with both Structured and Unstructured data
• Experience in Snowflake
• SFDC business/ technical knowledge
• Knowledge of Agile development methodology
• Working with at least one NoSQL system (HBase, Cassandra, MongoDB)
• Knowledge of databases, data warehouse platforms (Snowflake) and Cloud based tools.
• Experience in using data integration tools for ETL processes.
• Knowledge of Data Modelling techniques including schema design for both rational and NoSQL databases
• Understanding of Hadoop's ecosystem (including HDFS) and Spark for processing and analyzing large-scale datasets.
• Demonstrated experience in cutting-edge packages such as SciKit, TensorFlow, Pytorch, GPT, PySpark, Bit bucket etc.
• Ability to develop and communicate technical vision for projects and initiatives that can be understood by customers and management.
• Proven mentoring ability to drive results and technical growth in peers.
• Effective communication skills (verbal, written, and presentation) for interacting with customers and peers.
• Demonstrated application of statistics, statistical modeling, and statistical process control.

Benefits

• Access to dynamic career opportunities across different fields and industries
• Amazing opportunities for career growth
• Access to a world-class team of diverse experts