Analytics Engineer Hybrid

Join to apply for the Analytics Engineer (Full-Time)(Hybrid) role at Ortho Nebraska

The Analytics Engineer leverages analytics development and data engineering to make a meaningful impact in healthcare.

• Status:
  Full-Time
• Shift: Days
• Schedule:
  
  Mon - Fri:
  Five 8-Hour Shifts
• FTE /
  
  Hours:
  
  1.0 / 40

• Education:
  
  Bachelor's degree in Analytics, Computer Science, Mathematics, Statistics, or a related field required. Master's degree preferred.
• Licensure: N/A
• Certification: N/A
• Experience:
  
  5+ years of experience in data analytics or data engineering roles preferred. Exposure to financial and operational data, medical records, and information management systems preferred.

• Strong analytical skills, with experience in data manipulation, performance measurement.
• Excellent communication, presentation, and interpersonal skills, with the ability to engage and inform multidisciplinary teams.
• Proven time management skills, with the ability to manage multiple priorities and meet deadlines.
• Excellent problem‑solving and critical‑thinking abilities, with a keen attention to detail.
• Proficient with data visualization tools such as Power
  
  BI, Looker, or Tableau.
• Advanced SQL proficiency including dimensional modeling, complex queries, and BI optimization is required.
• Proficiency in programming languages such as Python, or R is preferred.
• Experience with cloud computing platforms like AWS, Azure, or Google Cloud preferred.
• Knowledge of data modeling, data warehousing, and data integration techniques preferred.
• Strong understanding of healthcare data standards, privacy regulations (e.g., HIPAA), and security best practices preferred.

• Data Modeling & SQL Development
  • Design and implement dimensional data models (star/snowflake schemas) optimized for analytics and BI consumption.
  • Write advanced SQL queries for complex business logic, aggregations, and calculations.
  • Develop and optimize SQL queries that feed BI platforms, ensuring performance at scale.
  • Validate data accuracy and integrity between source systems and analytics outputs.
  • Document data models, business rules, and technical specifications for stakeholder understanding.
  • Collaborate with Data Analysts to translate business requirements into technical data models.
• Business Intelligence Development
  • Design, develop, and maintain sophisticated BI dashboards for executive and operational audiences.
  • Build semantic models with advanced measures, calculated columns, and time intelligence functions.
  • Create data workflows to standardize and reuse data transformation logic across reports.
  • Support migration of existing Excel-based reports into interactive BI dashboards.
  • Monitor and enhance existing BI solutions for usability, performance, and alignment with evolving business needs.
• Collaboration
  • Collaborate with cross‑functional teams, including leadership, clinicians, and data professionals, to design and implement data‑driven solutions.
• Communicate findings and recommendations to stakeholders to drive informed decision‑making.
• Build and maintain strong working relationships with stakeholders to address evolving healthcare information needs.
• Work closely with IT and data governance teams to establish and enforce data quality standards and best practices.
• Promote data literacy and a self‑service approach to data, enabling stakeholders to access information they need.
• Contribute to multiple projects supporting organizational objectives using project‑management and process‑improvement skills.
• Provide data support and feedback for various initiatives, including ongoing metrics and dashboards, performance‑improvement efforts, and business case analysis.
• Professional Growth and Development
  • Stay current with advancements in healthcare industry & technology, data analytics, data engineering, cloud technology and regulatory requirements.
  • Seek opportunities for continuous skill and competency development.
  • Explore innovative analytical and machine‑learning tools with the goal of improving existing processes.
  • Support the planning, implementation, and monitoring of processes and systems to optimize data workflows.
  • Identify ways to…