Principal Engineer, Data

Role Description

As Principal Data Engineer, you will serve as Ensemble’s senior technical authority on data architecture — a high‑level individual contributor, not a people manager. You will assess data engineering practices across the organization, architect solutions that scale across teams, and establish a strong foundation for AI-driven capabilities across the organization.

You will architect and design a cloud-native data platform built on Azure and Databricks, enabling trusted, governed, and reusable data products that accelerate insight generation, operational automation, and emerging AI use cases. You will also own the organization’s data engineering technology roadmap, staying ahead of emerging tools and techniques and recommending what we should evaluate or adopt next.

This role serves as a technical escalation point and architectural authority for the Data Platform, influencing performance, scalability, cost optimization, developer experience, and long-term sustainability of Ensemble’s data ecosystem through credibility and technical judgment rather than formal authority.

Qualifications

• 10+ years of relevant job experience
• Deep experience designing and reviewing SQL‑based data models and transformations at enterprise scale.
• 3+ years working with big data technologies including but not limited to Databricks, SPARK, Azure, with a willingness and ability to learn new ones
• Excellent understanding of engineering fundamentals: testing automation, code reviews, telemetry, iterative delivery and DevOps
• Experience with polyglot storage architectures including relational, columnar, key-value, graph or equivalent
• Demonstrated ability to communicate effectively to both technical and non-technical, globally distributed audiences
• Solid foundations in formal architecture, design patterns and best practices
• Experience designing data platforms that support AI/ML, advanced analytics, or intelligent automation workloads.
• Deep experience with Azure cloud services and Databricks, including Spark‑based data engineering patterns.
• Proven ability to translate business needs into scalable data solutions.
• Experience owning or operating large‑scale cloud data platforms, including responsibility for cost optimization, performance tuning, and platform reliability.
• Demonstrated ability to scale data engineering through enablement, standards, and platforms, not just direct delivery.
• Strong understanding of Databricks pricing models, workload optimization, and Azure cloud cost drivers preferred.
• Demonstrated experience assessing data engineering practices across multiple teams or business units and translating findings into a concrete architectural or technology roadmap.
• Track record of evaluating emerging tools and technologies for real fit within an organization, and driving adoption decisions through credibility and clear communication rather than formal authority.

Requirements

• Must be inquisitive and demonstrate openness to innovation including AI to explore better processes and ways to alleviate friction and improve patient and client experiences.
• This is a remote position; however, candidates must be willing and able to travel to and work onsite at client, temporary, or corporate office locations as business needs require.

Benefits

• Comprehensive benefits package designed to support the physical, emotional, and financial health of you and your family, including healthcare, time off, retirement, and well-being programs.
• Investment in your professional development with opportunities for professional certification and tuition reimbursement.
• Quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company.