Driving Infinite Possibilities Within A Diversified, Global Organization
Honeywell is a Fortune 100 company with global sales surpassing $40B and has been one of Fortune’s Most Admired Companies for over a decade. Through innovation the Company brings together the physical and digital world to tackle some of the toughest societal and business problems – making the world a more productive, safe and sustainable place. The business is organized into five primary groups: Aerospace (including automotive); Home and Building; Performance Materials and Technologies; Safety and Productivity Solutions; and the Connected Enterprise. Honeywell specializes in things that are critically connected - beyond smart phones and laptops, we make the kinds of connections that keep cities working, planes flying, plants running, and workers safe. Our unique capabilities, over a century in the making, brings together data, expertise, and technology to connect people, processes, and assets. Our solutions our built-on top of our world class IoT Platform, Honeywell Sentience, and feature the latest in cyber security. Customers count on us to make and manage their critical connections.
The Principal Data Platform Architect is determined and assertive in both understanding SBG needs, as well as communicating Platform capabilities – both current and future. This role requires strong technical experience working with Hadoop Big Data ecosystems and tools such as Hive, Spark, etc. to understand and translate project requirements into technical requirements and solutions for the data engineering team to execute, architect and design our Big Data analytics platform that is scalable, optimized and fault-tolerant.
As Principal Data Platform Architect, you will:
•Lead, consult, and oversee multiple architectural engagements. Participate in setting strategy and standards through data architecture and implementation leveraging big data and analytics tools and technologies
•Work on highly complex projects that require in-depth knowledge within or across technical domains: technical, solutions, business or information.
•Lead domain specific architecture across multiple technical and functional domains, which includes coordinating the domain technical and business discussions relative to future data direction across multiple teams or complex product line.
•Analyze, design, and develop a roadmap and implementation plan based upon a current vs. future state in a cohesive data architecture viewpoint.
•Lead the research and evaluation of emerging data technology, industry and market trends to assist in project development and/or operational support activities to for multiple teams or complex scenarios.
•Perform program reviews to ensure that data design elements are reusable and repeatable across projects
•Define and develop guidelines, standards, and processes to ensure the highest data quality and integrity in the data stores residing on the data lake
•Work closely with business group engineers and product managers to understand their data requirements for existing and future projects on data analytics applications
•Work with IT and data owners to understand the types of data collected in various databases and data warehouses
•Research and suggest new toolsets/methods to improve data ingestion, storage, and data access in the analytics platform
•Provide guidance/mentor data engineering team, including code reviews
•Generate ad hoc sample implementation’s when needed
25 Lead, consult, and oversee multiple architectural engagements
25 Work with Hadoop Big Data ecosystems and tools
25 Ensure Big Data analytics platform is scalable, optimized and fault-tolerant
25 Set strategy & standards for data architecture and implementation leveraging big data & analytics
YOU MUST HAVE
•10+ Years of experience in Data Stacks & Data Platforms
•5+ years of hands-on technical experience in big data technologies
•Experience with CDC-based enterprise data ingestion technologies (Informatica, message queues, etc.)
•Hands-on proficiency in one or more scripting languages (e.g., Java, Python, Scala, R, Shell scripting)
•Experience with Hadoop data flow tools such as Sqoop, Flume, Flink and Nifi
•Experience with Hadoop workflow tools such as Spark and Spark streaming
•Experience consuming REST and WSDL services
•Experience working with databases and hands-on proficiency in SQL
•Experience with the Hortonworks Distribution
•Security configuration of Big Data stack. This includes LDAP, Kuberious configuration
•Apache Ranger Policy creation with Apache Atlas Integration
•Proficient in infrastructure set up on various cloud environments such as AWS, Azure
•Familiarity with data modeling, or MPP-style data warehouse technologies such as Hive, PostgreSQL
•Willingness to perform development and operations duties, sometimes requiring support during off-work hours
•Excellent written and verbal communication skills
•Experience with Agile project delivery frameworks and participating in Scrum ceremonies across a multi-disciplinary, matrixed environment
Exempt How Honeywell is Connecting the World
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, or veteran status.
Honeywell is an equal opportunity employer. Qualified applicants will be considered without regard to age, race, creed, color, national origin, ancestry, marital status, affectional or sexual orientation, gender identity or expression, disability, nationality, sex, religion, or veteran status.
For more information on applicable equal employment regulations, refer to the EEO is the Law poster .
Please refer to the EEO is the Law Supplement Poster & the Pay Transparency Policy .
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