Data Platform Engineer

The Data Platform Engineer is responsible for designing, building, and maintaining the university’s modern data platform, including data pipelines, data models, integrations, and analytics-ready datasets. This role supports Southeastern University’s ability to make timely, accurate, and informed decisions by ensuring that institutional data is reliable, accessible, secure, and well-governed.

This position works closely with Information Technology, Enterprise Applications, Data Analytics, Institutional Research, Enrollment, Advising, Financial Aid, Student Success, Finance, Advancement, and other university stakeholders to transform complex operational data into trusted data assets. The Data Platform Engineer will play a key role in helping the university move from reactive reporting and manual data processes toward a more proactive, customer-focused, and decision-driven data culture., * Design, build, and maintain scalable data pipelines that move data from core university systems into the university’s data warehouse, lakehouse, or analytics environment.

• Develop and maintain data models using SQL, dbt, and related modern data platform tools.
• Create reusable, governed, and analytics-ready datasets that support reporting, dashboards, operational workflows, and institutional decision-making.
• Support the continued development of the university’s data warehouse/data lake architecture.
• Build data structures that enable self-service analytics, AI-enabled workflows, and faster access to institutional insights.

Data Integration and Transformation

• Integrate data from university systems such as the student information system, CRM platforms, LMS, finance systems, advancement systems, housing systems, and other enterprise applications.
• Transform raw operational data into clean, standardized, and trusted data models.
• Translate business rules, source system logic, and operational processes into clear data transformations.
• Partner with application owners and business stakeholders to understand data definitions, system behavior, and reporting needs.
• Identify and resolve data inconsistencies, duplicate records, missing fields, and process-driven data quality issues.

Data Governance, Quality, and Documentation

• Develop and maintain documentation for data models, pipelines, business definitions, lineage, and transformation logic.
• Implement data quality checks, validation rules, and testing practices to increase trust in university data.
• Support institutional data governance practices, including data stewardship, access control, data classification, and consistent definitions.
• Promote standards for naming conventions, version control, deployment processes, and data modeling practices.
• Ensure data solutions are secure, FERPA-aware, well-documented, and aligned with university policy.

Analytics and Business Enablement

• Partner with data analysts, report developers, and university leaders to create datasets that support accurate and timely reporting.
• Support high-priority institutional areas such as enrollment, advising, financial aid, student clearance, student success, finance, advancement, and academic operations.
• Help reduce dependency on manual spreadsheets, one-off reporting, and disconnected departmental data processes.
• Build solutions that are practical, timely, focused, and aligned with the needs of university decision-makers.
• Assist in creating data products that help departments better understand performance, operations, trends, and opportunities.
• Operational Support and Continuous Improvement
• Monitor and troubleshoot data pipelines, scheduled jobs, integrations, and platform performance.
• Respond to data issues with urgency, accuracy, and clear communication.
• Identify opportunities to automate manual processes and improve data delivery.
• Participate in platform upgrades, migrations, security reviews, and technology modernization efforts.
• Stay current with emerging trends in data engineering, analytics, AI, cloud platforms, higher education technology, and data governance., All employees are responsible for maintaining an environment that is free from discrimination, intimidation, harassment, including sexual harassment., * SEU promotes a safe working environment. Employees are responsible for completing assigned tasks safely and efficiently, and supervisors are responsible for creating and maintaining a safe work environment.
• Employees must report any unsafe work conditions or practices, as well as any near-miss incidents, to their supervisor and Risk Management.
• Work-related injuries must be immediately reported to Security and Human Resources. When life or limb are at risk, please dial 911. Supervisors and employees should ensure that injury/accident reports are submitted to the Office of Human Resources within 24 hours of the incident.
• Emergency Employees report for or must remain at work in emergency situations. Dismissal or closure announcements do not apply to this position, unless instructed otherwise by your direct supervisor or a member of the Leadership Team.

The ideal candidate is technically strong, detail-oriented, service-minded, and able to bridge the gap between complex systems, institutional business processes, and practical data solutions., * Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field; equivalent professional experience may be considered.

Preferred Education:

• Master’s degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field; equivalent professional experience may be considered., * Experience building or supporting data pipelines, data warehouses, data lakes, or analytics platforms.
• Strong SQL skills and experience working with relational databases.
• Proficiency in Python for data processing, transformation, automation, or integration tasks.
• Experience transforming, modeling, and preparing data for reporting, analytics, or operational use.
• Experience with version control tools such as Git.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to understand complex business processes and translate them into data requirements.
• Ability to communicate technical concepts clearly to both technical and non-technical audiences.
• Strong commitment to data accuracy, documentation, security, and customer service.

Preferred:

• Experience with dbt or similar data transformation frameworks.
• Experience with cloud data platforms such as Snowflake, BigQuery, Redshift, Azure Synapse, Databricks, or similar technologies.
• Experience with ETL/ELT tools, APIs, integration platforms, orchestration tools, DLT, or scheduled data workflows.
• Experience with BI and reporting tools such as Power BI, Looker Studio, Tableau, or similar platforms.
• Experience working in higher education or with systems such as Jenzabar, Element451, Salesforce, Brightspace/D2L, Slate, Ellucian, Workday, or similar enterprise platforms.
• Familiarity with data governance, master data management, metadata documentation, and data quality testing.
• Experience supporting semantic layers, self-service analytics, AI-ready datasets, or institutional data products.
• Understanding of FERPA and data privacy expectations in a higher education environment., * Experience building or supporting data pipelines, data warehouses, data lakes, or analytics platforms.
• Strong SQL skills and experience working with relational databases.
• Experience transforming, modeling, and preparing data for reporting, analytics, or operational use.
• Experience with version control tools such as Git.
• Strong analytical, troubleshooting, and problem-solving skills.
• Ability to understand complex business processes and translate them into data requirements.
• Ability to communicate technical concepts clearly to both technical and non-technical audiences.
• Strong commitment to data accuracy, documentation, security, and customer service., * Office Environment: Ability to work primarily in an office setting, which involves sitting for extended periods.
• Computer Use: Proficiency in using computers for various tasks, which requires hand-eye coordination and manual dexterity for typing and handling office equipment.
• Communication: Strong verbal communication skills for meetings, presentations, and interactions with staff, students, and parents.
• Mobility: Capability to move around the office and campus as needed for meetings and events.
• Standing: Ability to stand and walk for extended periods of time for meetings and events.
• Lifting: Occasionally lift and carry items such as files, documents, or small office equipment weighing up to 20 pounds.
• Visual Requirements: Ability to read and interpret data on computer screens and printed documents.
• Hearing and Speaking: Adequate hearing to participate in conversations and phone calls, and clear speaking ability for effective communication.