Principal Data Platform Engineer (Databricks)

About the role

Prominence is seeking a Principal Data Platform Engineer to lead the design and delivery of scalable data solutions using Databricks and modern cloud ecosystems. This role involves shaping data strategy, designing solutions, and collaborating with clients and internal teams.

Responsibilities

• Own the end-to-end architecture and delivery of scalable data solutions, focusing 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 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.

Requirements

• 7+ years of experience in data engineering, with 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.
• Proven ability to lead technical delivery while remaining hands-on when needed.
• Proven 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 (Epic, HL7, FHIR, claims data) is strongly preferred.
• Experience with CI/CD, DevOps practices, and infrastructure-as-code tools is a plus.