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Minimum Data Set Jobs in Colorado (NOW HIRING)

Data Engineer

Highlands Ranch, CO · On-site

$116K - $140K/yr

Also contributes to curated modeling and semantic layer work under standards set by Analytics ... Minimum of three years of experience in data engineering, analytics engineering, business ...

Set up and configure PCs Required Skills / Qualifications: * Minimum of 3 years experience doing data migrations, imaging, refreshes * Minimum of 3 years of experience in basic technical hardware ...

A minimum of 4 full end-to-end SAP data migration implementations, with at least 2 involving S ... as set forth below. We anticipate this job posting will be posted until 10/16/2026. Accenture ...

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Senior Data & AI Platform Engineer

Denver, CO · On-site

$69.25 - $92.75/hr

You set the standards for platform reliability, CI/CD, environment design, security, and governance ... Minimum 6 years in data engineering, platform engineering, analytics engineering, or cloud ...

Minimum Experience: 1-3 years of progressive accounting experience * Required Technical Skills: Must have experience with: * Microsoft Excel and large data set manipulation * Journal entries, account ...

Temporary Data Reviewer

Aurora, CO · On-site

$25 - $35/hr

Minimum Qualifications: • Bachelor's degree in a scientific discipline or related field, or an ... The salary of the finalist(s) selected for this role will be set based on a variety of factors ...

Minimum Experience: 1-3 years of progressive accounting experience * Required Technical Skills: Must have experience with: * Microsoft Excel and large data set manipulation * Journal entries, account ...

Data Science Engineer

Westminster, CO · On-site

$100K - $140K/yr

Growth : Help shape the company culture, set the foundation for future success, and build world ... Minimum Qualifications BS or MS in Computer Science, Applied Mathematics, Statistics, Aerospace ...

Legal authorization to work in the United States Preferred Qualifications That Set You Apart ... This position will be open for a minimum of 7 days from the day of posting. Applicants are ...

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Showing results 21-40

Minimum Data Set information

What is a Minimum Data Set (MDS) coordinator?

Minimum Data Set (MDS) coordinators are healthcare professionals, often registered nurses, who are responsible for assessing and documenting the clinical needs of residents in long-term care facilities. They complete the federally mandated MDS assessments, which help determine care plans, reimbursement, and the quality of care provided to residents. MDS coordinators ensure that assessments are accurate, timely, and comply with regulations. Their work is crucial for maintaining facility compliance and optimizing resident outcomes.

What are the key skills and qualifications needed to thrive as a Minimum Data Set (MDS) coordinator?

To thrive as a Minimum Data Set (MDS) Coordinator, you need a strong background in nursing, detailed knowledge of care assessment processes, and typically a valid RN or LPN license. Familiarity with MDS software, electronic health records (EHRs), and regulatory compliance systems such as CMS guidelines is essential. Excellent organizational skills, attention to detail, and strong communication abilities help ensure accurate assessments and effective interdisciplinary collaboration. These skills are vital to ensure regulatory compliance, maximize reimbursement, and deliver high-quality patient care in long-term care settings.

What are some common challenges faced by Minimum Data Set (MDS) coordinators, and how can they be addressed?

MDS Coordinators often encounter challenges such as staying up-to-date with frequent regulatory changes, ensuring the accuracy of assessments, and managing tight deadlines. These challenges can be addressed by engaging in ongoing education, utilizing checklists and software tools to track assessments, and fostering strong communication with interdisciplinary team members. Building collaborative relationships with nursing staff and administrators also helps in streamlining processes and maintaining compliance with federal and state regulations.

What is the difference between Minimum Data Set vs Nursing Assistant?

AspectMinimum Data SetNursing Assistant
Required CredentialsCertification in healthcare assessment, often mandated for SNF staffCertified Nursing Assistant (CNA) certification
Work EnvironmentSkilled nursing facilities, long-term care, rehab centersHospitals, nursing homes, long-term care facilities
Employer & Industry UsageUsed by healthcare providers for patient assessments and care planningEmployers for direct patient care and support roles

The Minimum Data Set (MDS) is a comprehensive assessment tool used primarily in long-term care facilities to evaluate patient needs and plan care. Nursing Assistants (NAs) provide direct patient care and are often involved in implementing care plans based on MDS assessments. While both roles are integral to patient care in similar settings, MDS focuses on assessment and documentation, whereas NAs focus on hands-on care delivery.

What are the most commonly searched types of Minimum Data Set jobs in Colorado?

The most popular types of Minimum Data Set jobs in Colorado are:

What are popular job titles related to Minimum Data Set jobs in Colorado?

For Minimum Data Set jobs in Colorado, the most frequently searched job titles are:

What cities in Colorado are hiring for Minimum Data Set jobs?

Cities in Colorado with the most Minimum Data Set job openings:

Data Engineer

UDR

Highlands Ranch, CO • On-site

$116K - $140K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 6 days ago


Job description

UDR, Inc. is now hiring a Data Engineer to join our team.

**This is a hybrid position.**

GENERAL SUMMARY OF DUTIES: Builds and operates the data pipelines and conformed data models that bring source data into UDR’s enterprise data platform. Primary accountability is ingestion through the conformed layer: source system connectivity, pipeline build and reliability, raw data landing, and the conformed models that downstream analytics depend on. Also contributes to curated modeling and semantic layer work under standards set by Analytics Engineering, providing overlap and coverage across a small team. Works within the platform architecture, engineering, and deployment standards established by the Senior Data Platform Engineer, and partners with the Senior Snowflake Administrator, business analysts, software engineers, and quality assurance to deliver reliable, well-modeled data in support of UDR’s digital transformation applications.

ESSENTIAL FUNCTIONS:

  1. Build, operate, and maintain data ingestion pipelines that move data from internal systems, vendor systems, and third-party sources into the platform, including batch and incremental loads.
  2. Develop and maintain source system connectivity and integrations, including file-based loads and API-based interfaces in both real-time and batch contexts.
  3. Land and preserve raw source data in the platform so that original records remain traceable and reprocessable.
  4. Design, build, and maintain conformed data models, including schema design, cleansing, deduplication, and standardization logic that produce a reliable foundation for curated modeling.
  5. Implement and maintain orchestration, scheduling, and dependency management so that pipelines run in the correct order and downstream consumers receive data on time.
  6. Triage and resolve pipeline failures, monitor pipeline and data health, and implement alerting that identifies issues before downstream consumers are affected.
  7. Manage source schema changes, assessing downstream impact and coordinating updates with affected consumers before they break.
  8. Write advanced SQL for complex transformations and optimize query and pipeline performance, including cost-aware design of transformation logic.
  9. Implement automated data quality tests embedded in pipelines and models so that issues are surfaced before they reach curated layers.
  10. Contribute to curated dimensional models and semantic layer development under standards set by Analytics Engineering, providing overlap and coverage across the team.
  11. Contribute business context to entity definitions and conformance rules, working with Analytics Engineering, which owns those definitions.
  12. Maintain documentation of data definitions, lineage, and transformation logic sufficient for another engineer or an auditor to trace a reported number back to its source.
  13. Work within the platform architecture, coding, testing, and deployment standards established by the Senior Data Platform Engineer and help establish best practices for pipeline development and data modeling within those standards.
  14. Provide code reviews on pipeline, transformation, and model code, applying established standards consistently and giving actionable feedback.
  15. Support the Senior Snowflake Administrator on environment promotion, platform performance monitoring, and cost-aware workload design.
  16. Apply version control practices to all pipeline, transformation, and model code, including branching, pull request workflows, and peer review.
  17. Partner with business analysts on requirements, source to target mapping, and acceptance criteria for data work.
  18. Support quality assurance on reconciliation and pipeline validation testing and resolve defects identified during release validation.
  19. Participate in engineering design sessions and escalate design questions and platform gaps rather than working around them.
  20. Ensure data accuracy, quality, and security across all pipeline, modeling, and documentation work.
  21. Perform other duties as assigned or as necessary.

EDUCATION AND EXPERIENCE:

  1. Bachelor’s degree in computer science, data science, information systems, business with an information systems major, engineering, or related field; or equivalent combination of education and experience required.
  2. Minimum of three years of experience in data engineering, analytics engineering, business intelligence development, or a combination, with demonstrated expansion of scope over that time.
  3. Demonstrated experience building and operating production data pipelines, including ingestion from source systems, scheduling, dependency management, and failure handling, required.
  4. Knowledge of or experience interfacing with RESTful or SOAP APIs in both real-time and batch contexts preferred.
  5. Demonstrated experience building data models and analytics-ready datasets in a cloud data warehouse environment. Snowflake experience preferred.
  6. Working knowledge of layered data architecture, including the purpose of and boundaries between raw, conformed, and curated layers, with hands-on experience applying that pattern.
  7. Experience designing and implementing enterprise data solutions.
  8. Advanced SQL for complex transformation, performance tuning, and troubleshooting required.
  9. Experience with a modern SQL-based transformation framework, including model development, automated testing, and documentation.
  10. Working knowledge of a scripting language such as Python for pipeline development, data quality tooling, and automation preferred.
  11. Proficiency with version control and collaborative code review practices in a data or software context required.
  12. Exposure to semantic modeling and enterprise reporting for business audiences preferred.
  13. Experience supporting a migration from on-premises databases to a cloud data platform preferred.

Benefits Offered:

  • Medical, Dental, Vision Plans
  • Medical Flexible Spending Account
  • Dependent Care Spending Account
  • Lifestyle Spending Account
  • Supplemental Term Life Insurance
  • Critical Illness Plan
  • Supplemental Short-Term Disability Insurance / AD&D Insurance
  • Voluntary Long Term Care Insurance
  • 401(k) Plan with company match

Salary Range:
• $113,575-$133,618/yr., depends on experience

Bonus Potential:
• 10% annual bonus potential 

*UDR is proud to provide equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age