Principal Data Platform Engineer (Databricks)

Prominence Advisors is actively seeking a Principal Data Platform Engineer(Databricks) to join our team.Who We Are Prominence is a healthcare and life sciences technology and consulting firm dedicated to helping leading organizations do more with their data. With deep expertise across the full ecosystem — spanning providers, payers, and life sciences — we turn complex data into actionable insight.We deliver a full spectrum of services, including advisory, analytics, optimization, and IT staffing. Our work helps organizations operate more efficiently, improve patient outcomes, and deliver measurable financial impact through smarter use of data. Recognized as a 2x Best in KLAS organization, we partner with more than 120 health systems and 40 life sciences organizations, including 7 of the top 10 U.S. News & World Report-ranked institutions.Through our life sciences brands, Tegra Analytics and WLH Consulting & Learning Solutions, we extend these capabilities to pharmaceutical and biotech organizations — combining data, consulting, and learning to advance commercial excellence.By connecting strategy, data, and execution, we help organizations translate data into clarity, strategy into action, and vision into measurable results. At our core, we are a people-first, values-driven organization that believes strong teams and trusted partnerships are what ultimately make healthcare and life sciences smarter.Job SummaryProminence is looking for a Principal Data Platform Engineer to serve as a senior technical leader responsible for owning both the architecture and delivery of modern data platforms for our clients. This is a highly visible, client-facing role where you will shape data strategy, design scalable solutions, and lead implementation efforts end-to-end. You will partner directly with client stakeholders while mentoring internal team members, ensuring high-quality delivery aligned with Prominence’s standards of excellence. This role is ideal for someone who thrives at the intersection of strategy and execution—equally comfortable whiteboarding architecture with executives as they are building and optimizing pipelines alongside engineering teams. RequirementsEssential Functions and Responsibilities Own the end-to-end architecture and delivery of scalable data solutions, with a strong emphasis on Databricks-based platforms and modern cloud ecosystems Lead design and implementation of data pipelines, data models, and transformation frameworks that support analytics, reporting, and advanced use cases Serve as a primary client-facing technical leader, building trusted relationships and guiding stakeholders through complex data challenges and solution decisions Translate ambiguous business requirements into clear, actionable technical architectures and delivery plans Establish and enforce best practices across data engineering, including g data ingestion (pipeline orchestration, testing, and optimization) and DevOps. Drive platform strategy and architecture decisions, including lakehouse design, medallion architecture, and governance frameworks Lead and mentor delivery teams, providing technical guidance, code reviews, and hands-on support to ensure successful project outcomes Collaborate with cross-functional teams including data architects, analysts, and client stakeholders to ensure alignment and value delivery Identify risks, proactively address challenges, and ensure high-quality, timely delivery across engagements Contribute to internal capability building, including reusable frameworks, accelerators, and thought leadership Support business development efforts by shaping technical solutions, contributing to proposals, and participating in client discussions Minimum Qualifications 7+ years of experience in data engineering, with demonstrated progression into technical leadership and architecture ownership Deep expertise in Databricks and modern lakehouse architectures, including Delta Lake and Spark-based processing Advanced proficiency in SQL and Python, with strong experience building and optimizing large-scale data pipelines Hands-on experience with cloud platforms such as AWS, Azure, or GCP, including data services and infrastructure design Strong understanding of data modeling concepts, ETL/ELT patterns, and distributed data processing Experience with orchestration tools (e.g., Airflow) and transformation frameworks (e.g., dbt) Proven ability to lead technical delivery while remaining hands-on when needed Strong client-facing experience, including requirements gathering, solution design, and executive communication Ability to navigate ambiguity, prioritize effectively, and drive clarity in complex environments Healthcare data experience (e.g., Epic, HL7, FHIR, claims data) is strongly preferred Experience with CI/CD, DevOps practices, and infrastructure-as-code tools is a plus Skills, Knowledge, and Abilities Professional: Demonstrates a high degree of professionalism by treating others with respect, kee