Location:

\nCampus, ILLINOIS\n

Job Type:

\nFullTime\nJob Summary\nThe 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.\nFGCU 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.\nJob Description\nTypical duties include but are not limited to:\nPartners with stakeholders to determine data requirements and desired outcomes, translating strategic and operational needs into sustainable data engineering and analytics solutions.\nDesigns, 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.\nDevelops, 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.\nDesigns, develops, and maintains analytical and reporting data models that support complex statistical analysis, operational reporting, and institutional decision‑making.\nCollects, 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.\nAnalyzes data using quantitative and qualitative techniques to validate pipeline outputs, evaluate results, and support continuous improvement of analytics and reporting processes.\nDesigns, 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.\nCreates, 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.\nUtilizes appropriate statistical and analytical software to analyze and interpret data in support of reporting, assessment, and institutional research needs.\nReviews data engineering and analytics processes, evaluates outcomes, recommends improvements, and promotes best practices in data integration, data warehousing, analytics, and reporting.\nResearches, develops, and implements new techniques, tools, and procedures that enhance the university's data infrastructure, analytics capabilities, and reporting efficiency.\n

Other Duties:

\nCollaborates with other institutional departments to create and enforce data standards, definitions, coding and reporting practices.\nDevelops new techniques and procedures to enhance university analytics process.\nPerforms other duties as assigned.\nAdditional Job Description\n

Required Qualifications:

\nThis 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.\nExperience working with containerized development environments.\nExperience using SQL and Python.\nExperience supporting system-to-system data integration or data movement using relevant tools or technologies.\nExperience working with data systems that support reporting, analysis, and business decision-making.\nAny appropriate combination of relevant education, experience, and/or certifications may be considered.\n

Preferred Qualifications:

\nMaster's Degree from an accredited institution in Computer Science, Data Science, Data Engineering, Information Systems, or related field.\nExperience in systems analysis, process design, and end‑to‑end solution development in complex organizational environments, translating business needs into scalable technical solutions.\nExperience consuming and integrating data from RESTful APIs and external systems to support automated data ingestion and system interoperability.\nWork experience in higher education.\nExperience working with enterprise administrative systems such as Banner, Workday, or similar Student Information Systems or ERP platforms, including reporting, data integration, and database development.\nStrong experience using SQL and Python for data transformation, automation, validation, and development of scalable analytical workflows.\nExperience with Snowflake, including data ingestion, modeling techniques, performance tuning, cost optimization, and security configuration.\nExperience with the administration, architectural design, development, and support of reporting and analytics platforms used for dashboards, visual analytics, and self-service reporting.\nExperience designing, building, and maintaining data pipelines using Python, Docker, RESTful APIs, and Boomi.\n

Knowledge, Skills & Abilities:

\nKnowledge of data engineering, relational databases, SQL, data modeling, and cloud data warehousing concepts supporting analytics and reporting.\nKnowledge of data integration methods using APIs, enterprise integration tools (e.g., Boomi), and containerized environments (e.g., Docker) supporting scalable data workflows.\nKnowledge of data governance, data quality, and institutional reporting concepts, including enterprise systems (e.g., Banner, Workday) and BI tools (e.g., Tableau, Power BI).\nSkill in designing and maintaining data pipelines, data models, and analytical workflows using SQL, Python, APIs, and related tools.\nSkill in transforming, validating, and optimizing data within cloud data warehouse environments (e.g., Snowflake).\nSkill in developing dashboards, reports, and visual analytics using BI tools such as Tableau and Power BI.\nSkill in organizing and coordinating data engineering work, documenting processes, and managing multiple technical priorities.\nSkill in analyzing complex datasets, ing analytical reasoning, and communicating insights and recommendations clearly to both technical and non-technical audiences.\nAbility to translate business needs into technical data and reporting solutions.\nProven ability to think strategically and approach challenges with creativity.\nDemonstrated track record of reliability, meeting goals, and holding oneself accountable.\nStrong interpersonal skills and experience working effectively across teams.\nInstitutional Values & Behavioral Expectation\nIn this role, the successful candidate will be expected to:\nSeek out new approaches to improve outcomes; remain open to feedback and new ideas.\nLead with integrity; consistently produce high-quality work; persevere to overcome obstacles to meet deadlines and achieve deliverables.\nShare information and insights thoughtfully; build partnerships across departments; communicate respectfully; support colleagues to achieve common goals.\nPay Grade 19\nFGCU is a State University System of Florida member and an Equal Opportunity and Equal Access employer. 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