Data Analytics Engineer

Company: A national home healthcare group

Job Title: Data Analytics Engineer

Location: Hybrid - On-Site 2 days/week in Denver, CO

Job Type/Duration: Initial 5-month contract, with high likelihood of extension/permanent conversation based on the rate the team & company are growing.

Pay: $55-70/hour (with potential for flexibility based on experience)

Must-haves:

• ~5 years' experience
• Bachelor’s degree in Data Analytics, Data Science, Computer Science, or related field
• Proven experience in Data/Business Analysis
• SQL Proficiency (min 3 years)
• Strong understanding of data modeling, ETL processes, and data warehousing concepts.
• Must be comfortable and confident in project ownership rather than being assigned tasks to follow
• Excellent communication skills with a history of interfacing with executives and clients
• Willingness to travel: Max ~1 week/Quarter to St. Paul, Minnesota (plus light ad-hoc travel)
• Strong organizational skills with a focus on clear documentation
• DBT knowledge/expertise OR eagerness to learn & implement

Plusses:

• Snowflake
• Power BI or Tableau
• Experience with healthcare data, specifically claims data protected by HIPAA
• Knowledge of machine learning techniques and their application in data analytics
• Familiarity with version control systems (e.g., Git)
• Comfort working in an AGILE development environment
• Experience with Python programming

Day-to-day:

A national home healthcare client is seeking a skilled Data Analytics Engineer! This unique role involves collaborating with the parent company's data analytics team in Denver, Colorado and supporting a company brand out of Saint Paul, Minnesota. The ideal candidate will possess a strong foundation in data and business analytics, with a knack for understanding diverse business needs and translating them, in addition to building robust data models.

Key Responsibilities:

• Design, develop, and maintain scalable data pipelines and ETL processes to manage large volumes of structured and unstructured data
• Collaborate with data engineers, analysts, and business stakeholders to understand data requirements and translate them into actionable technical solutions
• Build and optimize data models for efficient data storage, retrieval, and analysis
• Implement and manage data governance practices to ensure data quality, accuracy, and consistency across all sources
• Collaborate and help to develop and maintain dashboards, reports, and data visualizations that provide actionable insights to various leadership teams
• Standardize data from various operational systems (EHR, Finance, Marketing CRM, and other databases) into models for business scorecards and management dashboards