Data Engineer II

The Data Engineer II supports data informed decision making by designing, building, and maintaining modern data pipelines, data models, and enterprise data warehousing solutions aligned with institutional goals. The role ensures reliable, scalable data ingestion, transformation, and delivery while maintaining high standards for data quality, integrity, and governance. It collaborates closely with functional and technical stakeholders to translate institutional and analytical requirements into sustainable data engineering solutions.

FGCU is building a culture of curiosity, commitment and collaboration. We value employees who successfully work with others and drive positive change through critical thinking and decisive action. If you thrive in an environment of innovation, accountability and mutual respect, you will find a good home here.

Job Description

Typical duties include but are not limited to:

• Partners with stakeholders to determine data requirements and desired outcomes, translating strategic and operational needs into sustainable data engineering and analytics solutions.
• Designs, builds, and maintains modern, automated data pipelines and system‑to‑system integrations to support reliable ingestion, transformation, and delivery of data using containerized services, scripting languages, APIs, and enterprise integration platforms such as Boomi.
• Develops, maintains, and optimizes enterprise data warehousing solutions within cloud‑based analytical platforms such as Snowflake, utilizing modern data modeling methodologies including Data Vault 2.0 and SQL‑based transformation and querying to support scalable, auditable analytics.
• Designs, develops, and maintains analytical and reporting data models that support complex statistical analysis, operational reporting, and institutional decision‑making.
• Collects, manages, validates, and cleans data from multiple internal and external sources; performs root‑cause analysis of data issues and develops documented standards, procedures, and controls to ensure ongoing data quality, integrity, and governance.
• Analyzes data using quantitative and qualitative techniques to validate pipeline outputs, evaluate results, and support continuous improvement of analytics and reporting processes.
• Designs, builds, and supports visual analytics, dashboards, and reporting solutions using business intelligence platforms such as Tableau and Power BI, enabled by well‑modeled and curated datasets.
• Creates, maintains, and updates complex reports, accreditation documentation, and assessment materials by ensuring the underlying data structures, warehouse models, and transformations are accurate, complete, and reliable.
• Utilizes appropriate statistical and analytical software to analyze and interpret data in support of reporting, assessment, and institutional research needs.
• Reviews data engineering and analytics processes, evaluates outcomes, recommends improvements, and promotes best practices in data integration, data warehousing, analytics, and reporting.
• Researches, develops, and implements new techniques, tools, and procedures that enhance the university’s data infrastructure, analytics capabilities, and reporting efficiency.

Other Duties:

• Collaborates with other institutional departments to create and enforce data standards, definitions, coding and reporting practices.
• Develops new techniques and procedures to enhance university analytics process.
• Performs other duties as assigned.

Additional Job Description

Required Qualifications:

• This position requires either eight years of directly related full-time experience or, as an alternative, a Bachelor’s degree from an accredited institution in an appropriate area of specialization and four years of full-time experience directly related to the job functions.
• Experience working with containerized development environments.
• Experience using SQL and Python.
• Experience supporting system-to-system data integration or data movement using relevant tools or technologies.
• Experience working with data systems that support reporting, analysis, and business decision-making.
• Any appropriate combination of relevant education, experience, and/or certifications may be considered.

Preferred Qualifications:

• Master’s Degree from an accredited institution in Computer Science, Data Science, Data Engineering, Information Systems, or related field.
• Experience in systems analysis, process design,