Senior Analytics Engineer

Jefferson Center for Mental Health
Denver, CO, United States
20 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
3 years minimum
Compensation
$94,100.0 - $116,700.0
Working hours
Regular working hours

Tech stack

Artificial Intelligence Business Analytics Applications Data Analysis Health Informatics Cloud Engineering Code Generation Information Systems Information Engineering Data Governance Data Mart Data Structures Data Warehousing
+22 more
Dimensional Modeling R (Programming Language) Information Retrieval Python (Programming Language) Performance Tuning Power BI Microsoft Copilot Azure Machine Learning SQL Databases Feature Store Azure Data Factory GitHub Copilot Retrieval-Augmented Generation Snowflake Data Layers AutoML Microsoft Fabric Information Technology Claude Restful APIs Data Pipelines Databricks

Job description

At Jefferson Center, it is our policy and our mission to be inclusive and mindful of the diversity of everyone who comes through our doors. We are passionate about building a community where mental health matters and equitable care is accessible to all races, ethnicities, abilities, socioeconomic statuses, ages, sexual orientations, gender expressions, religions, cultures, and languages.The Senior Analytics Engineer bridges data engineering, business intelligence, advanced analytics, and emerging AI capabilities. This role designs and develops trusted data products, enables self-service reporting, prepares data for predictive modeling and AI-applications, and partners with stakeholders to turn healthcare data into actionable insights. Applicants must be legally authorized to work in the United States. This position is not eligible for employer-sponsored work authorization now or in the future.Essential Duties:Analytics Engineering & Data ArchitectureDesign, develop, and maintain analytics-ready dimensional models (star schemas, semantic layers) and curated data marts.Translate business requirements into scalable, performant data structures that promote consistency across analytics solutions.Establish standards and best practices for data modeling, metric definitions, performance tuning, and data governance.Advanced Analytics & AI EnablementCurate feature tables and datasets for predictive modeling, time-series forecasting, risk scoring, and population health analysis.Prepare and optimize data pipelines and semantic layers for AI-driven experiences, Microsoft Fabric Copilots, and RAG/knowledge retrieval tools.Integrate automated ML and forecasting outputs into enterprise data structures for downstream reporting.Self-Service AnalyticsBuild user-friendly semantic models to support self-service analytics across Power BI, Microsoft Fabric, and modern cloud platforms.Educate and coach business users on report consumption, governance standards, and analytical tools.Business Partnership & Technical LeadershipCollaborate with clinical and operational leadership to identify high-value analytics opportunities and translate complex findings into business recommendations.Serve as a technical SME for analytics engineering, evaluating emerging cloud and AI technologies to elevate team maturity.Qualifications & Experience:EducationBachelor’s degree or higher in Analytics, Computer Science, Information Systems, or related quantitative field (or equivalent practical experience).Work Experience5+ years in Analytics Engineering, Data Engineering, or Senior BI/Data Modeling roles.3+ years in healthcare analytics. Experience with behavioral health, Medicaid, claims, or value-based care preferred.Core Technical SkillsExpert-level SQL, Python, R.Dimensional modeling (Kimball), star schemas, enterprise data warehouse architecture, semantic models.Experience with Azure Data Factory, Microsoft Fabric, dbt, Snowflake, Databricks, AzureML, REST APIsTime-series forecasting, trend analysis, exposure to Automated ML (AutoML), and predictive feature store construction.Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude) for code generation, documentation, and pipeline optimization.Note: Staff are held accountable for all duties of this job. This job description is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the job. Salary Range: $94,100 to $116,700*Jefferson Center pay is based on various factors including education level, licensure level, and years of relative experience.The salary listed above is based on 1.0 FTE (40 hours per week). Application Deadline: This position will remain posted until filled. We encourage applicants to apply by 10/16/2026 for priority consideration.

Requirements

Bachelor’s degree or higher in Analytics, Computer Science, Information Systems, or related quantitative field (or equivalent practical experience).

Work Experience

  • 5+ years in Analytics Engineering, Data Engineering, or Senior BI/Data Modeling roles.
  • 3+ years in healthcare analytics. Experience with behavioral health, Medicaid, claims, or value-based care preferred.

Core Technical Skills

  • Expert-level SQL, Python, R.
  • Dimensional modeling (Kimball), star schemas, enterprise data warehouse architecture, semantic models.
  • Experience with Azure Data Factory, Microsoft Fabric, dbt, Snowflake, Databricks, AzureML, REST APIs
  • Time-series forecasting, trend analysis, exposure to Automated ML (AutoML), and predictive feature store construction.
  • Proficiency with AI-assisted development tools (e.g., GitHub Copilot, Claude) for code generation, documentation, and pipeline optimization.

Benefits & conditions

Note: Staff are held accountable for all duties of this job. This job description is not intended to be an exhaustive list of all duties, responsibilities, or qualifications associated with the job.

Salary Range: $94,100 to $116,700*

*Jefferson Center pay is based on various factors including education level, licensure level, and years of relative experience.

*The salary listed above is based on 1.0 FTE (40 hours per week).

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