Principal Software Architect- Data Platform, Data

Ensemble Health Partners • Work at Home - Ohio - Other, OH

3d • $148,800 - $223,200 • Remote

About The Position

The Principal Software Architect is Ensemble’s senior technical authority for data platform engineering and is a high-level individual contributor, not a people manager. This is a software engineering role focused on applying professional software architecture discipline—including design patterns, modularity, repository structure, and system design—to a data platform built on Azure and Databricks. The architect will re-envision architectural patterns, assess engineering practices across the organization, and establish a foundation for AI-driven capabilities.

The role architects a cloud-native data platform that provides trusted, governed, and reusable data products to support insight generation, operational automation, and emerging AI use cases. It serves as a technical escalation point and influences software design, repository and branching strategy, CI/CD, performance, scalability, cost optimization, developer experience, and the long-term sustainability of the data ecosystem. The position also owns the technology roadmap and evaluates emerging tools and techniques for potential adoption.

The architect works across data engineering, analytics, data science, product, cloud, and platform teams. Through technical judgment and credibility rather than formal authority, the role sets standards, mentors senior and staff engineers, guides architectural decisions, and communicates recommendations to technical and executive stakeholders. The position is remote, with travel and onsite work at client, temporary, or corporate locations as business needs require. It is limited to people residing and authorized to work in the United States.

Requirements

• 10+ years of experience.
• Deep experience designing and reviewing SQL-based data models and transformations at enterprise scale.
• At least 3 years working with big data technologies, including technologies such as Databricks, Spark, and Azure; willingness and ability to learn new technologies.
• Excellent understanding of engineering fundamentals, including automated testing, code reviews, telemetry, iterative delivery, and DevOps.
• Experience with polyglot storage architectures, such as relational, columnar, key-value, or graph storage, or equivalent.
• Ability to communicate effectively with technical and non-technical audiences, including globally distributed audiences.
• Solid foundations in formal architecture, design patterns, and best practices.
• Hands-on software architecture experience and deep knowledge of design patterns, modular system design, and service/repository boundaries.
• Expert-level proficiency with Git and modern version control workflows, including trunk-based development, branching strategies, pull requests, and code reviews.
• Strong experience designing and implementing CI/CD pipelines and automated unit, integration, and data quality testing for software and data systems.
• Track record leading significant architectural refactors or platform re-platforming efforts that improve maintainability, reliability, or developer velocity.
• Experience designing data platforms for AI/ML, advanced analytics, or intelligent automation workloads.
• Experience owning or operating large-scale cloud data platforms, including cost optimization, performance tuning, and platform reliability.
• Ability to scale data engineering through enablement, standards, and platforms, not only direct delivery.
• Experience assessing data engineering practices across multiple teams or business units and translating findings into an architectural or technology roadmap.
• Ability to evaluate emerging tools and technologies for organizational fit and drive adoption through credibility and clear communication rather than formal authority.
• Inquisitiveness and openness to innovation, including AI, to explore better processes and improve patient and client experiences.
• Must reside and be authorized to work in the United States.
• Must be willing and able to travel to and work onsite at client, temporary, or corporate office locations as business needs require.

Nice To Haves

• Deep hands-on experience with Databricks and Azure cloud services, including Spark-based data engineering patterns.
• Experience operating data platforms in regulated or healthcare environments, including HIPAA, PHI, and data privacy considerations.
• Ability to translate business and clinical domain needs into scalable data solutions.
• Strong understanding of Databricks pricing models, workload optimization, and Azure cloud cost drivers.

Responsibilities

• Re-envision data platform architectural patterns, retire legacy approaches, and replace them with modern, modular system design.
• Assess data pipelines, platforms, and engineering practices across the organization to identify inefficiencies, technical debt, risks, and improvement opportunities.
• Architect scalable, secure, and cost-efficient data solutions across teams and business domains using Databricks and Azure.
• Define service and repository boundaries, interfaces, and design patterns that keep the platform modular, testable, and maintainable.
• Serve as a technical escalation point for difficult data engineering problems, including systemic reliability issues in tier-1 pipelines and datasets.
• Define and evolve Git workflows, branching strategies, and pull request standards for data platform repositories.
• Establish and champion CI/CD pipelines that automate testing, validation, and deployment of data pipelines and platform code.
• Drive adoption of automated unit, integration, and data quality testing.
• Define and evolve data engineering standards, patterns, and architectural guardrails across engineering teams.
• Establish and evolve platform architecture for AI, machine learning, and advanced analytics workloads, including feature readiness, training data quality, lineage, and observability.
• Partner with Data Science, Analytics, Product, and Cloud teams to support model development, deployment, and monitoring while managing operational and governance risks.
• Define and enforce AI-ready data standards for quality, metadata completeness, schema stability, and data timeliness.
• Evaluate emerging data and AI tools, frameworks, and techniques for organizational fit; run proofs of concept and technical spikes before recommending adoption.
• Author and maintain a data engineering technology roadmap aligned with business priorities, explaining trade-offs, costs, and adoption sequencing.
• Present roadmap recommendations and business impacts to technical and executive stakeholders.
• Treat enterprise datasets as data products with clear ownership, quality guarantees, documentation, and usage metrics.
• Establish standards and guardrails to optimize compute efficiency, storage utilization, query performance, and pipeline reliability.
• Partner with Finance, Cloud, and Engineering leaders on Databricks and Azure FinOps, including budgets, usage monitoring, cost transparency, and proactive optimization.
• Use cost-to-serve, workload efficiency, platform SLAs, utilization trends, and other metrics to guide platform decisions.
• Ensure platform-level observability for workload performance, cost drivers, usage patterns, and capacity forecasting.
• Mentor senior and staff engineers in architecture, system design, and software craftsmanship without formal management responsibility.
• Lead code and design reviews that raise engineering standards.
• Influence technical direction across teams through credibility, clear communication, and sound technical judgment.
• Collaborate with data engineering, analytics, data science, and platform/infrastructure teams to align architecture with business goals.
• Provide exceptional experiences for clients, patients, and colleagues; embrace innovation; and deliver outstanding results.
• Perform other job-related duties as required by the supervisor, subject to reasonable accommodation.

Benefits

• Comprehensive benefits package supporting physical, emotional, and financial health, including healthcare, time off, retirement, and well-being programs.
• Professional development investment, including a relevant professional certification for each associate.
• Tuition reimbursement.
• Quarterly and annual incentive programs for employees who exceed expectations.
• Work-life flexibility.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed