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