Analytics Engineer
About The Position
Join Joyce University in transforming healthcare education by building a trusted data foundation for reporting, insights, and data-driven decision-making. As an Analytics Engineer, you will transform data from multiple sources into clean, reliable datasets and develop models, metrics, and tools to help teams understand and use data effectively. You will collaborate with university teams to translate their reporting and analytical needs into scalable data models, standardized metrics, and meaningful insights, supporting self-service analytics, institutional reporting, strategic planning, and everyday decision-making. This role is crucial in helping a growing university leverage data to advance healthcare education and support the student journey.
Requirements
- Bachelor’s degree in a quantitative field or equivalent practical experience.
- Strong SQL skills and experience working with relational data models.
- Experience with data transformation tools, such as dbt or similar frameworks.
- Experience transforming raw data into clean, reliable, and well-documented datasets.
- Familiarity with modern data warehouses and ELT/ETL pipelines.
- Solid understanding of data modeling, metrics design, and data quality best practices.
- Experience translating business requirements into scalable analytical solutions.
- Strong analytical thinking, attention to detail, and communication skills.
Responsibilities
- Design, build, and maintain analytics-ready data models that support reporting, dashboards, and advanced analysis.
- Transform raw data from multiple sources into clean, reliable, and well-documented datasets.
- Translate business requirements into technical data models, metrics, and KPIs.
- Develop and maintain semantic layers, standardized metrics definitions, and documentation.
- Optimize data models for performance, scalability, and long-term maintainability.
- Contribute to analytics engineering standards, tooling, and data governance practices.
- Extract, transform, and load (ETL) data from diverse data sources and systems.
- Build and maintain automated pipelines, scripts, and workflows for data ingestion and transformation.
- Partner closely with data engineers to define data pipelines, schemas, and best practices.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Apply statistical, analytical, and modeling techniques to generate actionable insights.
- Design and deliver interactive dashboards and reports for stakeholders.
- Communicate insights clearly to both technical and non-technical audiences.
- Enable self-service analytics by supporting business users with trusted datasets and metrics.
- Ensure data quality, consistency, and reliability through testing, validation, and monitoring.
- Identify, investigate, and resolve data discrepancies and quality issues.
- Implement data quality controls to support accurate and trustworthy analytics.
Benefits
- Self-directed paid time off
- 12 paid holidays
- Medical, dental, and vision insurance
- Employer-paid short-term and long-term disability coverage
- 401(k) retirement plan
- Professional development opportunities
- Continuing education opportunities
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
