Sr Platform Engineer, Data

Thank you for considering a career at Ensemble!

Ensemble is a leading provider of technology-enabled revenue cycle management solutions for health systems, including hospitals and affiliated physician groups. They offer end-to-end revenue cycle solutions as well as a comprehensive suite of point solutions to clients across the country.

Ensemble keeps communities healthy by keeping hospitals healthy. We recognize that healthcare requires a human touch, and we believe that every touch should be meaningful. This is why our people are the most important part of who we are. By empowering them to challenge the status quo, we know they will be the difference!

O.N.E Purpose:

• Customer Obsession: Consistently provide exceptional experiences for our clients, patients, and colleagues by understanding their needs and exceeding their expectations.

• Embracing New Ideas: Continuously innovate by embracing emerging technology and fostering a culture of creativity and experimentation.

• Striving for Excellence: Execute at a high level by demonstrating our “Best in KLAS” Ensemble Difference Principles and consistently delivering outstanding results.

The Opportunity:

JOB SUMMARY 

By embodying our core purpose of customer obsession, new ideas, and driving innovation, you will help ensure that every touchpoint is meaningful and contributes to our mission of redefining the possible in healthcare.

As a Senior Platform Engineer, you are a hands-on technical engineer who sits at the intersection of data engineering, cloud platform, and networking — building the infrastructure and pipelines that make Ensemble's data platform reliable, secure, and scalable. You will design and implement Azure-based platform solutions, author data pipelines, harden network architecture, and apply solid software engineering discipline across everything you ship.

This is primarily a delivery role. You will spend the majority of your time writing code, configuring infrastructure, reviewing pull requests, and solving hard operational problems — not managing people or setting org-wide strategy. You bring strong opinions about platform reliability, cloud cost, and network security, and you translate those opinions into running systems.

We are open to strong cloud/platform engineers who want to go deep on data, and to strong data engineers who have grown into platform and networking responsibility. What matters is that you have done hard, hands-on work at the intersection of these disciplines — you understand both why a pipeline fails and why a Private Endpoint DNS record is wrong, and you are comfortable owning both.

JOB COMPETENCIES 

Platform & Cloud Engineering — Designs, builds, and operates Azure-based platform infrastructure — compute, storage, networking, identity, and security — with a bias toward infrastructure as code, repeatability, and operational simplicity; balances speed of delivery with platform reliability and cost efficiency.

Data Engineering Depth — Delivers scalable, well-tested data pipelines and transformations on Databricks and Azure Data Factory; applies sound data modeling, performance tuning, and data quality discipline as standard practice rather than afterthoughts.

Network & Security Awareness — Understands Azure networking constructs — VNets, subnets, NSGs, Private Endpoints, DNS, and ExpressRoute/VPN — and applies them correctly in platform design; proactively identifies and closes network attack surface without creating unnecessary friction for engineering teams.

Software Engineering Craft — Writes clean, testable, maintainable code; participates actively in code and design reviews; treats CI/CD and automated testing as the default way of working; holds a high bar for version control hygiene and deployment safety.

Operational Ownership — Takes end-to-end accountability for the platform components and pipelines in scope — from initial design through production monitoring, incident response, and continuous improvement; does not hand off and walk away.

Technical Communication — Communicates clearly with both engineering peers and non-technical stakeholders; can explain complex networking or data platform trade-offs to a product manager or a VP without losing the audience or oversimplifying the substance.

Continuous Learning & AI Fluency — Stays current with the Azure, Databricks, and data engineering ecosystem; consistently applies generative AI tools to accelerate engineering work, improve code quality, and troubleshoot complex systems.

ESSENTIAL JOB FUNCTIONS 

Customer Obsession, New Ideas, Striving for Excellence

• Consistently deliver high-quality platform and data solutions that improve the reliability, speed, and accuracy of data reaching internal and external stakeholders.

• Apply generative AI tools in day-to-day engineering work to accelerate development, improve code quality, troubleshoot complex systems, and design scalable solutions.

Data Pipeline & Platform Engineering

• Design, build, test, deploy, monitor, and continuously improve scalable data pipelines using Azure Data Factory, Databricks, Apache Spark, and Python.

• Implement Delta Lake patterns on Azure Data Lake Storage (ADLS) including table design, schema evolution, Z-ordering, VACUUM, and partition strategies.

• Build and maintain event-driven integrations using Azure Service Bus, Event Hub, and Azure Functions to support real-time and near-real-time data flows.

• Implement data quality monitoring frameworks — row counts, schema validation, null checks, freshness SLAs — as first-class pipeline components.

• Develop reusable pipeline templates and platform abstractions that accelerate delivery across the data engineering team.

• Translate product and business requirements into incremental, testable technical deliverables with clear acceptance criteria.

Azure Cloud Platform & Infrastructure

• Provision and manage Azure infrastructure using infrastructure as code (Terraform, Bicep, or ARM templates), treating all platform configuration as version-controlled code.

• Design and operate Azure-native services including Azure Data Factory, Azure Databricks, Azure Data Lake Storage Gen2, Microsoft Fabric (or Synapse), Azure Key Vault, and Azure Monitor.

• Manage identity and access controls using Azure Active Directory, Managed Identities, RBAC, and Unity Catalog — applying least-privilege principles across all platform components.

• Implement platform-level observability: pipeline SLAs, workload performance dashboards, alerting, and cost tracking via Azure Monitor, Log Analytics, and Databricks system tables.

• Contribute to FinOps practices by monitoring compute costs, right-sizing clusters, configuring auto-termination policies, and flagging cost anomalies.

• Support containerized workloads running on Azure Kubernetes Service (AKS) where data platform components require container-based deployment patterns.

Networking & Security

• Design and implement secure Azure networking architectures for data platform workloads — VNets, subnets, NSGs, Private Endpoints, Private DNS Zones, and service endpoints — eliminating unnecessary public internet exposure for PaaS services.

• Configure, troubleshoot, and document Private Link connectivity across Azure PaaS services (ADLS, Azure SQL, Key Vault, Event Hub, Databricks); diagnose DNS resolution issues and routing problems end-to-end.

• Apply encryption-in-transit and encryption-at-rest standards; maintain TLS configurations, key rotation policies, and secret management practices in line with security baselines; participate in security reviews and threat modeling for new platform components.

• Partner with Cloud and Infrastructure teams on hub-and-spoke or landing zone network topologies; configure and validate firewall rules and IP allowlisting in a way that balances security posture with engineering team productivity.

CI/CD, DevOps & Engineering Standards

• Build and maintain CI/CD pipelines in Azure DevOps that automate testing, validation, and deployment of data pipelines, notebooks, and infrastructure code.

• Follow and actively contribute to branching strategies, pull request standards, and code review practices; flag gaps or inconsistencies in existing workflows and propose improvements.

• Write unit, integration, and data quality tests as standard deliverables — not optional additions after the feature is shipped.

• Contribute to engineering standards and pattern libraries, ensuring consistency across pipelines and reducing onboarding friction for new team members.

Software Engineering & Architecture

• Write well-structured, maintainable Python and SQL code; apply design patterns, modular decomposition, and API design principles appropriate to the problem at hand.

• Participate in design sessions and architecture discussions, contributing hands-on perspective on what is feasible and what the operational implications of design choices will be.

• Conduct thorough code and design reviews that raise the engineering bar across the team.

• Identify and address technical debt within owned platform components in a planned, incremental way.

Cross-Functional Collaboration & Mentorship

• Partner with data engineering, analytics, data science, and cloud/infrastructure peers to deliver integrated platform solutions.

• Provide mentorship to junior and mid-level engineers through code reviews, pair programming, and technical guidance.

• Communicate platform capabilities, limitations, and trade-offs clearly to product and business stakeholders.

EMPLOYMENT QUALIFICATIONS 

Required Skills & Experience

• 6+ years of hands-on engineering experience, with meaningful time spent across data engineering and cloud platform or infrastructure domains.

• 3+ years working with Microsoft Azure services in a production environment (ADF, ADLS Gen2, Databricks, Azure Functions, Service Bus, Event Hub, Azure Monitor).

• 2+ years of hands-on Azure networking experience: VNets, NSGs, Private Endpoints, Private DNS, service endpoints, and firewall configurations.

• 2+ years developing with Apache Spark and Databricks, including Delta Lake table design, schema evolution, and performance optimization.

• 4+ years of production SQL development — complex transformations, query tuning, indexing, and data modeling at enterprise scale.

• Strong Python development skills applied to data engineering, pipeline orchestration, or platform tooling.

• Demonstrated experience with infrastructure as code (Terraform preferred; Bicep or ARM acceptable).

• Hands-on experience building and maintaining CI/CD pipelines in Azure DevOps; familiarity with trunk-based development and pull request workflows.

• Experience with event-driven architectures using Azure Service Bus, Event Hub, or equivalent messaging platforms.

• Working knowledge of Azure identity and access management: Azure AD, Managed Identities, RBAC, and Key Vault. 

• Strong understanding of engineering fundamentals: automated testing, code reviews, telemetry, iterative delivery, and DevOps.

Preferred Qualifications 

• Familiarity with data platform security and governance: Unity Catalog, column-level security, data masking, and audit logging.

• Background in software engineering (APIs, microservices, or distributed systems) that informs platform design and operationalization decisions.

• Experience with polyglot storage architectures: relational, columnar (Parquet/Delta), key-value, or graph systems.

• Exposure to healthcare datasets; familiarity with HL7 or EDI standards is a plus.

• Experience supporting AI/ML or advanced analytics workloads — feature stores, training data pipelines, or model serving infrastructure.

• Familiarity with AKS, container networking, and Kubernetes-based workload deployment patterns.

• Azure certifications relevant to the role (e.g., AZ-305, DP-203, AZ-700) are a plus, but not a substitute for demonstrated hands-on experience.

• Familiarity with FinOps practices, Databricks cost management, and Azure cost optimization tooling.

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.

WORKING CONDITIONS 

• Remote-friendly with periodic travel for team meetings, onsite collaboration, or client engagements.

• General office environment or work from home.

• May require occasional off-hours support for platform incidents or scheduled maintenance windows.
• This position pays between $101,600 – $152,400 based on experience
• 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.

#LI-SA1
#LI-REMOTE

Join an award-winning company

Five-time winner of “Best in KLAS” 2020-2022, 2024-2025

Black Book Research's Top Revenue Cycle Management Outsourcing Solution 2021-2024

22 Healthcare Financial Management Association (HFMA) MAP Awards for High Performance in Revenue Cycle 2019-2024

Leader in Everest Group's RCM Operations PEAK Matrix Assessment 2024

Clarivate Healthcare Business Insights (HBI) Revenue Cycle Awards for strong performance 2020, 2022-2023

Energage Top Workplaces USA 2022-2024

Fortune Media Best Workplaces in Healthcare 2024

Monster Top Workplace for Remote Work 2024

Great Place to Work certified 2023-2024

• Innovation
• Work-Life Flexibility
• Leadership
• Purpose + Values

Bottom line, we believe in empowering people and giving them the tools and resources needed to thrive. A few of those include:

• Associate Benefits –  We offer a 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. 
• Our Culture – Ensemble is a place where associates can do their best work and be their best selves. We put people first, last and always. Our culture is rooted in collaboration, growth, and innovation.  
• Growth – We invest in your professional development. Each associate will earn a professional certification relevant to their field and can obtain tuition reimbursement. 
• Recognition – We offer quarterly and annual incentive programs for all employees who go beyond and keep raising the bar for themselves and the company. 

Ensemble is an equal employment opportunity employer. It is our policy not to discriminate against any applicant or employee based on race, color, sex, sexual orientation, gender, gender identity, religion, national origin, age, disability, military or veteran status, genetic information or any other basis protected by applicable federal, state, or local laws.  Ensemble also prohibits harassment of applicants or employees based on any of these protected categories.

Due to business, operational, payroll, and regulatory requirements, this position is limited to individuals who reside and are authorized to work within the United States. Applications generated from outside the United States will not be considered.  Individuals may reapply when located within the United States.

Ensemble provides reasonable accommodations to qualified individuals with disabilities in accordance with the Americans with Disabilities Act and applicable state and local law. If you require accommodation in the application process, please contact TA@ensemblehp.com.

This posting addresses state specific requirements to provide pay transparency.  Compensation decisions consider many job-related factors, including but not limited to geographic location; knowledge; skills; relevant experience; education; licensure; internal equity; time in position.  A candidate entry rate of pay does not typically fall at the minimum or maximum of the role’s range.

Employment Disclaimers – Ensemble