Data Engineer III (Onsite in Denver, CO)

Alpine Physician Partners•Denver, CO

1d•$93,226 - $137,966•Hybrid

About The Position

The Data Engineer III is a senior-level data engineer role and is responsible for designing & building data pipelines for enabling value-based healthcare, population health management, and enterprise analytics. The data engineer will design, develop, maintain, and support 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 & building modern data pipelines & features for delivery of AI agentic solutions. This position will also bridge the gap between on premise, SQL-based Data Warehousing solution 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.

Requirements

Applicants must be authorized to work in the United States without the need for current or future visa sponsorship.
Minimum 6 years of experience required in creating robust enterprise-grade data engineering pipelines using SQL, Python, Apache Spark, ETL, ELT, Databricks Technology Stack, Azure Cloud Services, Cloud-based Data and Analytics platforms required. 8-10 years preferred.
Minimum 3 years of experience required in solution design blueprinting and leading technical team members towards delivery of robust enterprise-grade data platform solutions.
Strong proficiency in SQL and data analysis required.
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
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 & 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.)

Nice To Haves

Experience in distributed data (structured, semi-structured, unstructured, streaming) processing techniques using Apache Spark, Hadoop, Hive, Kafka, and big data ecosystem technologies preferred.
Experience in data modeling and design for data warehouse, relational databases, and NoSQL data stores 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

Responsibilities

Owns solution design blueprints and architecture of the enterprise data platform features and functionality, including data ingestions, data integrations, data pipelines, data models, data quality, data governance.
Plays technical leadership role and leads other team members and guides 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, NoSQL databases.
Enable designing, 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 recommending new data features in conjunction with 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 to federal and state laws and regulations
Other duties as assigned