Principal Data Engineer
Title: Principal Data EngineerWork Location: Eagan, MNWork Arrangement: HybridPosition Overview:As the Principal Data Engineer, you will serve as the most senior technical contributor on the Data Platform Engineering team. This role is responsible for providing technical leadership, influencing architecture and engineering standards, and designing scalable data solutions that support analytics, automation, and future AI initiatives. You will partner with architects and engineering teams to design modern cloud-based data platforms and solve complex technical challenges in a hands-on capacity.Key Responsibilities:Provide technical leadership and architectural guidance for enterprise data engineering initiativesEstablish engineering standards, design patterns, and best practices across the data engineering organizationMentor and coach data engineers through technical guidance, design reviews, and code reviewsDesign, develop, and implement scalable cloud-based data engineering solutionsBuild and optimize data pipelines supporting ingestion, transformation, orchestration, and deliveryPartner with Product Owners and business stakeholders to translate business requirements into scalable technical solutionsServe as the technical escalation point for complex production issues and data engineering challengesDrive continuous improvement of engineering processes, tooling, and development standardsPrimary Requirements:8+ years of professional data engineering experience designing and delivering enterprise-scale data solutionsHealthcare or health insurance industry experienceExpert-level Python and SQL with extensive experience building scalable ETL/ELT pipelinesStrong cloud data engineering experience using AWS or equivalent enterprise cloud platforms (Azure or GCP)Experience processing large datasets using Spark, PySpark, Spark SQL, or similar distributed processing technologiesProven ability to design end-to-end data engineering solutions including ingestion, transformation, orchestration, automation, and data qualityStrong understanding of cloud-native data architectures and modern data engineering best practicesDemonstrated experience influencing technical direction, architecture decisions, and engineering standardsExperience mentoring engineers and leading technical discussions across teamsExcellent communication skills with both technical and non-technical stakeholdersAbility to work independently while driving complex technical initiatives.Desired Skills:Hands-on Databricks experience including notebooks, workflows, and cluster managementExperience with AWS services including S3, Lambda, Glue, Step Functions, SQS, IAM, and CloudWatchExperience with AI-enabled data platforms, automation, or machine learning data pipelinesInfrastructure-as-Code experience using TerraformCI/CD pipeline experience using GitLab or similar toolsExperience with streaming technologies such as Kafka, MSK, or KinesisFHIR or healthcare interoperability experienceAWS Solutions Architect or Data Engineer Certification.