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Principal IT Analyst at Honeywell

Phoenix, Arizona, United States -

Full Time

Start Date

Immediate

Expiry Date

26 Aug, 26

Salary

0.0

Posted On

28 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Informatica PowerCenter, IDMC/IICS, ETL Architecture, SQL, Oracle, MS SQL Server, Control-M, Redwood, Data Warehousing, PL/SQL, UNIX Shell Scripting, Data Modeling, Azure, AWS, SDLC, Erwin

Industry

Automation Machinery Manufacturing

Description

As Principle ETL Data (IT) Analyst in Data Integration Platform organization at Honeywell, you will have opportunity to lead and work with large footprint of various data integration technologies and make a difference by establishing a solid foundation for innovation, performance, reliability, and scalability working on on-prem and public cloud solutions leveraging multiple data integration technologies. You will lead the Informatica platform and application development, architecture, and operations that are responsible for setting the strategy and delivering a scalable and reliable data platform that supports Honeywell’s Digital Platform and Applications. Additionally, you will also participate and provide your guidance for the design and implementation of ETL mappings, governance of production jobs in global high availability and fast paced high-performance environments. You will be responsible to maintain various data models across all applications, design new solutions at the cutting edge of data technology and will deliver large scale systems that will have an impact on revenue growth. You will report directly to our Sr. Director, IT and you’ll work out of our Phoenix, AZ or Charlotte, NC locations on a Hybrid work schedule. Hybrid Work Schedule Note: For the first 90 days, New Hires must be prepared to work 100% onsite M-F

Responsibilities

Lead the Informatica platform development, architecture, and operations to deliver a scalable data platform for Honeywell's Digital Platform. Design and implement ETL mappings and maintain data models to support revenue growth and high-performance environments.