Data Engineer

ECPI University is hiring an onsite Data Engineer to design, build, and take ownership of end-to-end pipelines and modeled datasets for its Snowflake data platform. In this hands-on role, you will collaborate closely with the Senior Director of Solution Architecture while helping modernize how data is integrated, transformed, governed, and used across the institution.

What you’ll do

• Design, build, and own end-to-end pipelines that ingest data from enterprise SaaS applications, student systems, and operational databases into Snowflake, choosing the right approach across batch, API extraction, change data capture, and near real-time streaming.
• Implement transformation logic in SQL and Python as version-controlled, tested, and documented code, with orchestration for both scheduled and event-driven workloads.
• Partner on 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, translating needs from academic, enrollment, financial aid, student services, and administrative stakeholders into durable models.
• Establish certified datasets as the authoritative source for key institutional measures, retiring redundant reports and manual extracts they replace.
• Own operational reliability for assigned pipelines, including monitoring, alerting, incident response, and root cause analysis, and implement automated data quality tests for freshness, completeness, uniqueness, and business rules.
• Tune Snowflake for performance and cost, including warehouse sizing, clustering, query optimization, and resource monitors, while implementing role-based access control, masking, and least-privilege access consistent with FERPA, GLBA, and University policy.
• Run CI/CD for data platform code using GitHub Actions or comparable tooling, with automated build, test, deployment, environment promotion, rollback, and automated tests enforced as a deployment gate.
• Manage data platform objects as code to keep environments reproducible and changes reviewable, replacing manual data movement, reconciliation, and hand-run reports with automation.
• Set standards for AI-assisted engineering practice, including effective prompting, rigorous review of generated code, accountability for output ownership, and contributing to University governance for AI-assisted development.
• Design and implement solutions using Snowflake native AI capabilities such as Snowflake Cortex functions, embeddings, and vector search, and advise when a native capability is the right choice versus an external service.
• Mentor the Associate Data Engineer and other colleagues through code review, pairing, and instruction, and define standards and reference implementations used by the team.
• Communicate technical tradeoffs clearly to 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 experience with roles, grants, and masking policies, and demonstrated ability to diagnose and resolve performance and cost issues.
• Advanced SQL (window functions, CTEs, incremental and merge patterns), plus proficiency in Python for data engineering and working knowledge of dimensional modeling.
• Experience with dbt or a comparable modular, tested approach to SQL transformations, and orchestration tooling such as Airflow, Dagster, Azure Data Factory, or Snowflake tasks.
• Experience with ETL/ELT tooling for ingestion and orchestration, such as Snowflake Openflow (Apache NiFi), Snaplogic, Fivetran, Matillion, or a comparable integration platform.
• Demonstrated CI/CD experience for data or software delivery using GitHub Actions, Azure DevOps, or comparable tooling, 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 describe where these tools accelerate work and where they can mislead.
• Ability to resolve ambiguity independently and communicate clearly with functional stakeholders in an Agile (Scrum) environment.

Helpful background (preferred)

• SnowPro Advanced Data Engineer or SnowPro Core certification, or hands-on experience with Snowflake Cortex, embeddings, or vector search.
• Experience in Azure or AWS (storage, identity, and secrets management) or infrastructure as code such as Terraform.
• Higher education experience, including student information systems, learning management systems, 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.

Compensation and benefits

Base salary: $105,000 to $128,000 per year (midpoint near $115,000).

• Tuition scholarship program for full-time employees and 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

Location and working conditions

Location: Virginia Beach, VA (onsite). This is not a remote position.

Physical demands are representative of those required to perform essential job functions. The employee must be able to communicate professionally 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 for individuals with disabilities.