Associate Data Engineer

Good Faith Pay Range: In accordance with Virginia law, the good-faith pay range for this position is $70,000 – $82,000 per year. Actual compensation will be determined based on the candidate's qualifications, education, experience, skills, and other legitimate business factors.

Position Summary

The Associate Data Engineer supports the development and maintenance of ECPI University's cloud data platform, built on Snowflake. Working under the Senior Director of Solution Architecture and alongside experienced engineers, this position builds and maintains the pipelines that move information from the University's enterprise systems into Snowflake, where it supports reporting, analytics, and institutional decision making. Faculty, academic leadership, and student support staff rely on this data to advise students, monitor academic progression, and report accurately within a highly regulated environment.

This is an entry-level position designed for a recent graduate. Structured mentorship, regular code review, and a defined progression path toward the Data Engineer level are part of the role.

Key Responsibilities

Pipeline Development and Support

• Build and maintain data ingestion and transformation pipelines that load data from enterprise source systems into Snowflake, following established architectural patterns and standards.
• Write, test, and tune SQL for data transformation, validation, and reconciliation.
• Support scheduled data loads, monitor job execution, and escalate failures with clear diagnostic detail.

• Reconcile data between source systems and Snowflake to confirm completeness and accuracy.
• Build and run automated data quality checks, and document exceptions for resolution.
• Investigate reported data discrepancies, trace them to their origin, and communicate findings clearly.

• Use AI coding assistants, such as GitHub Copilot, as a routine part of daily work, validating every generated query, transformation, or script before committing it. The engineer, not the tool, is accountable for correctness.
• Submit work through pull requests in GitHub and keep changes moving through the automated build, test, and deployment process.
• Automate recurring manual tasks rather than repeating them, and apply the platform's native AI capabilities, such as Snowflake Cortex, under the direction of senior engineers.
• Follow University guidelines for AI-assisted development, including how sensitive student and institutional data is kept out of external tools.

• Document pipeline logic, data lineage, and table definitions so that colleagues can maintain and extend the work.
• Participate in code review, design discussions, and Agile (Scrum) ceremonies, and work with analysts and functional staff to confirm that delivered data sets meet the stated need.
• Build depth in Snowflake, SQL, and Python through mentorship and structured learning, including certification such as SnowPro Core with University support.
• Perform other duties as assigned.

• Bachelor's degree in Computer Science, Data Science, Information Systems, Analytics, or a related field. Recent graduates are encouraged to apply.
• Zero to two years of professional experience. Internships, co-ops, capstone projects, and applied coursework are considered relevant.
• Working knowledge of SQL, including joins, aggregation, and subqueries, with the ability to reason about whether a query returned the right answer.
• Foundational understanding of relational database concepts and data modeling.
• Familiarity with Python or a comparable language used in data work.
• Version control with Git, including branching and pull requests, and willingness to work within a code review process.
• Practical use of AI coding assistants with sound validation judgment. Candidates should be able to describe a case where a tool produced a plausible but wrong answer and how they caught it.
• Understanding of CI/CD concepts and willingness to work where automated tests must pass before code is deployed.
• Strong attention to detail, clear written and verbal communication, and sound judgment in handling sensitive student and institutional data.

• Exposure to Snowflake or another cloud data platform through coursework, certification, or hands-on work.
• Exposure to dbt, ELT or ETL tooling, or automated data testing frameworks.
• Exposure to GitHub Actions, Azure DevOps, or another CI/CD platform.
• Exposure to Azure or AWS cloud services, or to a business intelligence tool such as Power BI or Tableau.
• Awareness of FERPA or comparable data privacy requirements in a regulated environment.

The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. The employee is required to professionally communicate in person, over the telephone, and through email; move about the school and offices; handle various types of media and equipment; and visually observe and assess. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

ECPI University is proud to be an Equal Opportunity Employer.