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Metro location and common data-engineering role with moderate employer brand produce medium competition.
Data engineering skills (SQL, Python, ETL) are highly transferable across industries.
Requires specific data engineering skills and tooling but no explicit years requirement.
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Own the production and governance of certified, clean, and timely datasets supporting Academic reporting, analytics, automation, and customer services.
Collaborate across teams to understand requirements, maintain data workflows, manage Alteryx Server environment, and standardize integration of legacy and diverse systems.
Drive data quality assurance, documentation, and adherence to governance standards while mentoring junior engineers on best practices.
Proficiency in SQL and programming languages such as Python and R.
Experience with complex data structures, ETL processes, and troubleshooting data workflows.
Familiarity with Git-based workflows for managing data pipelines and code.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in delivering governed, certified data workflows that support analytics and automation in academic or similar domains.
Demonstrated ability to manage multiple projects and collaborate effectively with cross-functional teams including analysts and stakeholders.
Comfortable working with data governance, workflow automation tools (e.g., Alteryx Server), and integrating data across diverse systems.