ironquill.tech/board

$ cat jobs/principal-data-engineer-is-remote-providence-eaf4a2f3c180.json

Principal Data Engineer IS - Remote

providence·US·United States·senior
pythonjavac#snowflakesqlawsazuredevopsgit
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Providence is seeking a highly experienced Principal Data Engineer to lead the evolution of the organization's enterprise data platform strategy, architecture, governance framework, and modernization initiatives. This role will serve as the technical leader responsible for defining data standards, driving Snowflake platform maturity, establishing governance and metadata practices, and completing the migration of legacy data assets into a scalable, governed, and reusable enterprise data ecosystem. The successful candidate will combine deep technical expertise with strategic leadership to create the architectural foundations, engineering standards, and operating model required to support the next generation of enterprise analytics, reporting, AI, and data products. Required Qualifications: Bachelor's Degree in Computer Engineering, Computer Science, Mathematics, Engineering or, equivalent educ/experience 8 years Related experience; software development preferred with increasing scope and responsibilities. Extensive experience with object-oriented programming in C#, Java, Python or equivalent. Experience with source code control systems such as Git and how to successfully use them in across multiple teams. Extensive SQL integration development experience with SQL/noSQL. Extensive experience with Agile software development methodologies and tools such as Azure DevOps, TFS, and Jira. Proven track record of working both independently and collaboratively as part of a multi-disciplined team. Extensive experience with Azure/AWS/hybrid and other cloud technologies. Experience designing and successfully implementing a highly complex project. Preferred Qualifications: 1. Enterprise Data Architecture Design enterprise data models and platform standards. 2. Data Governance & Metadata Management Define ownership, lineage, metadata, and data quality standards. 3. Legacy Migration & Data Refactoring Lead database migrations, consolidation efforts, and data modernization programs. 4.

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