BI ETL Data Developer II or III
Job in
Oxford, Butler County, Ohio, 45056, USA
Listed on 2026-05-02
Listing for:
Miami University
Full Time
position Listed on 2026-05-02
Job specializations:
-
IT/Tech
Data Engineer, Data Analyst, Data Science Manager, Data Warehousing
Job Description & How to Apply Below
Job Description Summary
The Business Intelligence ETL Data Developer II develops, maintains, and supports scalable data pipelines and analytics solutions that enable data-informed decision-making across the University. In this role, you will take ownership of data pipelines and contribute directly to advancing modern data engineering practices within a cloud-based data ecosystem. You will collaborate with stakeholders and technical partners to deliver reliable, high-performing solutions, with a focus on data quality, maintainability, and continuous improvement.
EssentialDuties BI ETL Data Developer II
- Develop, maintain, and enhance data pipelines using modern ELT tools (e.g., dbt, Fivetran, Airflow, or similar) in a cloud-based environment.
- Write, optimize, and maintain SQL and/or Python-based transformations that support scalable analytics solutions.
- Monitor, troubleshoot, and resolve issues in production data pipelines to ensure reliability, performance, and data integrity.
- Implement data validation, testing, and quality checks to improve the consistency and trustworthiness of data assets.
- Collaborate with stakeholders and technical partners to translate business needs into scalable data solutions.
- Support and improve existing data integrations and workflows with a focus on maintainability and performance optimization.
- Contribute to and follow best practices for version control, testing, and deployment (CI/CD).
- Create and maintain documentation for data pipelines, models, and system processes.
- Contribute to team practices that support consistent delivery and continuous improvement.
- Stay current with emerging data tools and practices and apply them to improve team outcomes.
- Design, develop, and optimize scalable data pipelines using modern ELT tools (e.g., dbt, Fivetran, Airflow, or similar) in a cloud-based environment.
- Lead the development of advanced SQL and/or Python-based transformations supporting enterprise analytics and reporting.
- Own production data pipelines, including monitoring, performance tuning, troubleshooting, and ensuring reliability and data integrity.
- Design and implement robust data validation, testing, and quality frameworks to ensure trusted data at scale.
- Design scalable data models and transformation patterns to support enterprise reporting and analytics needs.
- Partner with stakeholders to translate complex business requirements into sustainable, high-impact data solutions.
- Drive improvements to existing data pipelines and processes to enhance performance, scalability, and maintainability.
- Lead adoption of best practices for version control, testing, deployment, and operational support (CI/CD).
- Develop and maintain comprehensive documentation for data pipelines, models, and architecture.
- Guide team practices that support consistent delivery, operational excellence, and continuous improvement.
- Mentor team members and contribute to the growth of technical standards and capabilities across the team.
- Bachelor’s degree in computer science, information technology, or a relevant field earned by date of hire with two to four or more years of relevant experience
- Associate’s degree in computer science, information technology, or a relevant field earned by date of hire and four to six or more years of relevant experience
- Ability to analyze complex data and develop practical, scalable solutions.
- Ability to troubleshoot and resolve data pipeline and data quality issues in a timely manner.
- Ability to translate business needs into effective technical data solutions.
- Ability to communicate technical concepts clearly to both technical and non-technical audiences.
- Ability to work collaboratively across teams and build effective working relationships.
- Ability to manage multiple priorities and adapt to changing requirements in a dynamic environment.
- Ability to document solutions and processes to support maintainability and knowledge sharing.
- Ability to design scalable, maintainable, and efficient data solutions that support enterprise needs.
- Ability to diagnose and resolve complex…
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