Sr. Data Engineer - Computing Services

Carnegie Mellon University is a private, global research university that stands among the world’s most renowned educational institutions. With groundbreaking brain science, path-breaking performances, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the curious to deliver work that matters, your journey starts here!

We seek a Senior Data Engineer to join our dynamic data team. This role will be integral to supporting the university’s data initiatives, with the mission of eliminating data silos and developing services that enable the strategic use of institutional data for informed decision-making and growth. We focus on dataset curation, data pipeline creation & optimization, system integrations, supporting advanced analytics, and championing data governance and quality. In this role, you will work closely with other technology teams and campus partners to execute and deliver data-related products, fostering an environment where university-wide cross-functional teams thrive through proactive engagement and collaboration.

The ideal candidate will have substantial expertise in data engineering and analysis. The Senior Data Engineer will support and enhance data products, collaborating with business partners, cross-functional teams, and departments such as Finance, Human Resources, the Office of the VP of Research, and Enrollment Management to understand technical requirements and workflows. They will develop and optimize data pipelines, implement and manage integrations, and support advanced analytics initiatives. Success in this position will hinge on the candidate's ability to collaborate effectively and implement the technical requirements that further the growth of our data community.

Your core responsibilities will include:

• Design, develop, and maintain scalable data pipelines and systems for data integration, processing, and storage.

• Implement and manage data models to support analytics and reporting needs.

• Develop and optimize ELT/ETL processes to ensure data quality and integrity.

• Collaborate with AI engineers to integrate machine learning models into data pipelines.

• Perform data analysis to support decision-making and strategic initiatives.

• Integrate data sources into platforms such as Snowflake, Tableau, or Power BI.

• Monitor and administer data engineering infrastructure.

• Identify and mitigate data security and privacy risks.

• Participate in the evaluation of new products and industry standards.

• Work with noisy, dirty, and unstructured data to cleanse, scrape, and convert it into structured data.

• Design and implement scalable, performant data pipelines, data services, and data products.

• Build and architect solutions from a framework perspective to ensure reusability rather than building siloed solutions.

• Figure out problems with limited direction, using intuition to anticipate issues and opportunities.

• Understand, use, and create REST-oriented APIs.

• Other duties as assigned.

Flexibility, excellence, and passion are vital qualities within Computing Services. Inclusion, collaboration, and cultural sensitivity are valued competencies at CMU. Therefore, we are in search of a team member who is able to effectively interact with a varied population of internal and external partners at a high level of integrity. We are looking for someone who shares our values and who will support the mission of the university through their work.

You must demonstrate:

• Expertise in data engineering, including data pipeline development and optimization, ETL/ELT processes, and data integration.

• Experience in data modeling and database design.

• Proficiency in SQL and experience with RDBMS systems such as Snowflake, Microsoft SQL Server, Oracle, or PostgreSQL.

• Knowledge of data visualization tools such as Power BI or Tableau.

• Collaborate with AI engineers to integrate machine learning models into data pipelines.

• Strong data analysis skills and experience with statistical analysis tools.

• Proficiency in programming languages such as Python, SQL, etc.

• Experience with MPP databases like Redshift or Snowflake.

• Understanding of structured and unstructured data.

• Experience with DBT is a plus.

• Knowledge of building and managing data warehouses

• Experience with cloud services (AWS, Azure, Google Cloud)

Qualifications:

• Bachelor’s Deg