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Senior Analytics Engineer Jobs in Colorado (NOW HIRING)

Jefferson Center

Senior Analytics Engineer

Wheat Ridge, CO · On-site

$94K - $116K/hr

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 ...

IPL (Indiana)

Senior Engineer, Analytics

Louisville, CO · On-site

AES Clean Energy (CE) is seeking a Senior Analytics Engineer to support the Operations and Maintenance (O&M) Engineering team in building the data analytics architecture to support the future growth ...

Digible

Senior Analytics Engineer

Englewood, CO · On-site

$103K - $141K/yr

The Role Digible is looking for a Senior Analytics Engineer to join our team! Our Data team owns the platform and analytics that power Fiona and the decisions made across Digible -- from ingestion ...

BillGO

Senior AI Data Analytics Engineer

Fort Collins, CO · On-site

$132K - $196K/yr

Senior AI Data Analytics Engineer. Why This Role Matters BillGO's future runs on trustworthy data, and this role owns making sure it stays that way as the company scales. As the architect of the data ...

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Senior Analytics Engineer information

See Colorado salary details

$62.6K

$133.1K

$193K

How much do senior analytics engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for senior analytics engineer in Colorado is $133,077.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,900.00 and $150,900.00 per year, depending on experience, location, and employer.

What is a senior analytics engineer?

A Senior Analytics Engineer is a data professional who bridges the gap between data engineering and data analysis. They design, build, and maintain data pipelines, data models, and analytics infrastructure to ensure that data is reliable, accessible, and well-structured for analysis. Typically, they work with tools like SQL, dbt, and cloud data warehouses, collaborating closely with data analysts and business stakeholders to deliver actionable insights. Their role often involves optimizing data workflows, implementing best practices, and mentoring junior team members.

How does a senior analytics engineer typically collaborate with data scientists and business stakeholders?

Senior Analytics Engineers play a vital role in bridging the gap between raw data and actionable insights. They work closely with data scientists to ensure that data pipelines and models are robust, scalable, and well-documented. Additionally, they frequently meet with business stakeholders to understand reporting needs and translate them into technical requirements, ensuring that analytics solutions align with organizational goals. This collaborative approach helps maintain data quality and accelerates the delivery of meaningful analyses across teams.

What are the key skills and qualifications needed to thrive as a senior analytics engineer, and why are they important?

To thrive as a Senior Analytics Engineer, you need strong expertise in data modeling, SQL, data warehousing, and analytics, typically backed by a degree in computer science, mathematics, or a related field. Proficiency with tools such as dbt, Python, cloud data platforms (like Snowflake or BigQuery), and experience with BI tools are commonly required, along with certifications in analytics or cloud technologies being a plus. Excellent problem-solving, communication, and stakeholder management skills help you translate business requirements into robust data solutions. These skills ensure data integrity, drive actionable insights, and support effective decision-making across the organization.

What is the difference between Senior Analytics Engineer vs Data Engineer?

AspectSenior Analytics EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, Analytics, or related; SQL, Python, data visualization skillsBachelor's/Master's in CS, Data Engineering, or related; SQL, Python, ETL tools skills
Work EnvironmentFocus on data analysis, reporting, and insights; collaborates with data teams and business unitsFocus on data pipeline development, infrastructure, and storage; works closely with data infrastructure teams
Employer & Industry UsageUsed across tech, finance, healthcare, and retail for analytics rolesCommon in tech, finance, and data-driven industries for building data systems

While both roles require strong SQL and Python skills, Senior Analytics Engineers primarily focus on analyzing data, creating reports, and deriving insights for business decisions. Data Engineers build and maintain the data infrastructure, pipelines, and storage systems. The roles often collaborate but serve different functions within data teams.

What are the most commonly searched types of Analytics Engineer jobs in Colorado?

The most popular types of Analytics Engineer jobs in Colorado are:

What are popular job titles related to Senior Analytics Engineer jobs in Colorado?

For Senior Analytics Engineer jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Senior Analytics Engineer jobs in Colorado look for?

The top searched job categories for Senior Analytics Engineer jobs in Colorado are:

What cities in Colorado are hiring for Senior Analytics Engineer jobs?

Cities in Colorado with the most Senior Analytics Engineer job openings:

Senior Analytics Engineer jobs near you
Infographic showing various Senior Analytics Engineer job openings in Colorado as of August 2026, with employment types broken down into 92% Full Time, 4% Part Time, 1% Temporary, and 3% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $133,077 per year, or $64 per hour.

Senior Analytics Engineer

Wheat Ridge, CO • On-site

Jefferson Center
See more jobs at Jefferson Centerexternal

$94K - $116K/hr

Full-time

Posted 21 days ago

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 Architecture

  • Design, 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 Enablement

  • Curate 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 Analytics

  • Build 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 Leadership

  • Collaborate 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:

Education

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.

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 9/10/2026 for priority consideration.

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