Data Engineer III

Are you looking to work for a company that has been recognized for over a decade as a Top Place to Work? Apply today to become a part of a company that continues to commit to putting our employees first. Job Description Applicants must be authorized to work in the United States without the need for current or future visa sponsorship. Location Position is onsite with a possible hybrid in Denver, Colorado. Position Summary The Data Engineer III is a senior‑level data engineer role and is responsible for designing and building data pipelines for enabling value‑based healthcare, population health management, and enterprise analytics. The data engineer will design, develop, maintain, and support a cloud‑based (Microsoft Azure) big data platform using modern data engineering design patterns and tools. This position will also play a key enabler role in designing and building modern data pipelines and features for delivery of AI agentic solutions. It also bridges the gap between on‑premise SQL‑based data warehousing and the Azure Databricks Lakehouse architecture, learning and supporting the existing proprietary system while working with technical leaders to further develop plans to migrate to a cloud‑based solution. Essential Functions Owns solution design blueprints and architecture of the enterprise data platform features and functionality, including data ingestion, data integration, data pipelines, data models, data quality, and data governance. Plays a technical leadership role and leads other team members, guiding them on solution design blueprints, data solutions development, and best practices for our enterprise data platform. Designs, builds and maintains scalable, automated data pipelines to enable reporting, data visualization, advanced analytics, data science, and machine‑learning solutions. Supports critical data pipelines with a scalable distributed architecture, including data ingestion (streaming, events, and batch), data integration (ETL, ELT, Azure Data Factory), and distributed data processing using Databricks Data & Analytics and Azure Cloud Technology Stacks. Builds cloud data solutions using multiple technologies, such as SQL, Python, Data Lake (Databricks Delta Lake), Cloud Data Warehouse (Azure Synapse), RDBMS, and NoSQL databases. Enables design, implementation, and fine‑tuning of AI applications including LLMs, RAG pipelines, and prompt engineering solutions for clinical and operational use cases. Addresses issues in data flow logic and data model design, as well as the interoperability of new datasets with existing data models. Participates in and conducts code‑reviews for all changes to the codebase and conveys coding standards clearly and concisely. Tests work on each assignment before working with product owners to ensure business requirements are fulfilled. Coordinates identification of requirements and recommends new data features in conjunction with the development manager, product owners, and department managers. Acts as a subject‑matter expert by sharing information and providing support and training to others, as well as spearheading team projects and establishing goals and milestones for projects. Ensures goals and commitments to the team are met. Adheres to the company’s compliance program and federal and state laws and regulations. Other duties as assigned. Knowledge, Skills and Abilities Minimum 6 years of experience creating robust enterprise‑grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks technology stack, Azure Cloud Services, and cloud‑based data and analytics platforms. 8–10 years preferred. Minimum 3 years of experience in solution design blueprinting and leading technical team members toward delivery of robust enterprise‑grade data platform solutions. Strong proficiency in SQL and data analysis. Experience in distributed data (structured, semi‑structured, unstructured, streaming) processing techniques using Apache Spark, Hadoop, Hive, Kafka, and big‑data ecosystem technologies. Experience in data modeling and design for data warehouse, relational databases, and NoSQL data stores. Ability to mentor others. Excellent verbal and written communication skills. Great customer service skills. Great teamwork and leadership skills. Independent problem‑solving skills. Self‑motivated and self‑managed. Proficient in Microsoft Office Suite. Qualifications Bachelor’s degree in computer science, information systems, or equivalent work experience. 7+ years working with the following concepts and technologies: Modern data platforms, such as Databricks and Azure Data Factory. Modern data engineering design and development using Python and SQL. Relational and dimensional data models, T‑SQL, Microsoft SQL Server, etc. Data integration strategies and supporting technologies. Electronic data exchange (FHIR, HL7, CSV, EDI, etc.). Minimum 6 years of experience creating robust enterprise‑grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks technology stack, Azure Cloud Services, and cloud‑based data and analytics platforms. 8–10 years preferred. Experience migrating on‑premise data warehousing solutions to Azure solutions (preferred). Experience with Visual Studio and .NET technologies such as C# (preferred). Experience working with common health‑care datasets (preferred). Experience working on an agile/scrum‑driven software development team. Home office that is HIPAA compliant for all remote or telecommuting positions as outlined by the company policies and procedures. Salary Range Base Salary Range: $93,225.60 – $137,966.40 Additional Compensation: Eligible for an annual bonus based on individual and/or company performance. Benefits Includes medical, dental, and vision insurance; 401(k); paid time off (PTO); and Employee Assistance Program (EAP). Application Deadline Open until filled. Applications will be reviewed on a rolling basis. How to Apply Apply via the careers page at #J-18808-Ljbffr