Data Engineer

Join ECPI University onsite in Virginia Beach, VA and help shape an end-to-end Snowflake data platform used for institutional analytics. In this hands-on Data Engineering role, you will design and own pipelines, modeled datasets, and reliability, while working closely with the Senior Director of Solution Architecture. You will also collaborate with colleagues through code review and mentoring, and influence how AI-assisted engineering is governed and validated across the team.

What you’ll work on

• Design, build, and own end-to-end pipelines that ingest data from enterprise SaaS applications, student systems, and operational databases into Snowflake, using the right approach for each source across batch, API extraction, change data capture, and near real-time streaming.
• Develop transformation logic in SQL and Python as version-controlled, tested, documented code, with orchestration for scheduled and event-driven workloads.
• Contribute to platform architecture with the Senior Director of Solution Architecture, including layering strategy, standards, and reusable patterns.
• Create dimensional, analytics-ready data models that support reporting, analytics, and downstream integrations, turning requirements from academic, enrollment, financial aid, student services, and administrative stakeholders into durable models.
• Establish certified data sets that serve as the authoritative source for key institutional measures, replacing redundant reports and manual extracts.
• Own operational reliability for assigned pipelines: monitoring, alerting, incident response, and root cause analysis, plus automated data quality testing for freshness, completeness, uniqueness, and business rules.
• Tune Snowflake for both performance and cost, including warehouse sizing, clustering, query optimization, and resource monitors; implement role-based access control, masking, and least-privilege access aligned with FERPA, GLBA, and University policy.
• Own CI/CD for data platform code, using GitHub Actions (or comparable tooling) for automated build, test, and deployment with environment promotion, rollback, and automated tests as a deployment gate.
• Manage data platform objects as code so environments are reproducible and changes are reviewable, reducing manual data movement, reconciliation, and hand-run reporting.
• Support AI-assisted engineering standards through effective prompting, rigorous review of generated code, and clear accountability for owned output; contribute to University governance for AI-assisted development.
• Design and implement solutions using Snowflake’s native AI capabilities, including Snowflake Cortex functions, embeddings, and vector search, and advise when a native capability is appropriate versus an external service.
• Mentor an Associate Data Engineer and other colleagues through code review, pairing, and direct instruction; define standards and reference implementations.
• Communicate technical tradeoffs clearly to both technical and non-technical audiences, including IT leadership, and perform other duties as assigned.

What you bring

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field (or equivalent combination of education and experience), plus 4+ years of professional data engineering experience, including 2+ years hands-on in Snowflake.
• Production Snowflake depth across virtual warehouses, micro-partitioning, clustering, streams and tasks, Snowpipe, and time travel, plus roles, grants, and masking policies, with demonstrated ability to diagnose and resolve performance and cost issues.
• Advanced SQL (window functions, common table expressions, incremental and merge patterns), strong Python for data engineering, and working knowledge of dimensional modeling.
• Experience with dbt or a comparable modular, tested approach to SQL transformation, and orchestration tooling such as Airflow, Dagster, Azure Data Factory, or Snowflake tasks.
• Experience with ETL/ELT ingestion and flow orchestration such as Snowflake Openflow (Apache NiFi), Snaplogic, Fivetran, Matillion, or comparable tooling.
• CI/CD experience for data or software delivery through GitHub Actions, Azure DevOps, or comparable tools, including automated data testing enforced in the pipeline.
• Daily, practical use of AI coding assistants in production engineering with a disciplined validation habit, including the ability to explain where tools accelerate work and where they can mislead.
• Ability to resolve ambiguity independently and communicate clearly with functional stakeholders in an Agile (Scrum) environment.

Compensation and benefits

• Salary range: $105,000 to $128,000 annually (midpoint near $115,000).
• Tuition scholarship program available to full-time employees and their immediate family members after 90 days of employment.
• Competitive compensation and medical and dental benefit plans.
• PTO and holiday pay.
• 401(k) participation with possible employer contributions.

Working conditions

This is an onsite role in Virginia Beach, VA. The physical demands described are representative of those required to perform essential functions, including professional communication in person, by telephone, and by email, moving about school and office environments, handling various types of media and equipment, and visually observing and assessing. Reasonable accommodations may be made to enable individuals with disabilities to perform essential functions.

Preferred qualifications

• SnowPro Advanced Data Engineer or SnowPro Core certification, or hands-on experience with Snowflake Cortex, embeddings, or vector search.
• Experience with Azure or AWS, including storage, identity, and secrets management, or infrastructure as code such as Terraform.
• Higher education experience, particularly student information systems, learning management systems, or institutional reporting, or integration of a major HCM, ERP, or enrollment CRM platform.
• Experience establishing AI-assisted development standards for a team, or mentoring junior engineers.