Sr Platform Engineer, Data

Ensemble Health Partners • Work at Home - New Jersey - Other, NJ

6d • $101,600 - $152,400 • Remote

About The Position

Ensemble is hiring a hands-on Senior Platform Engineer who works at the intersection of data engineering, cloud platforms, and networking. The role builds infrastructure and pipelines to make the company’s data platform reliable, secure, and scalable. The engineer designs and implements Azure-based platform solutions, authors data pipelines, strengthens network architecture, and applies sound software engineering practices. This is primarily a delivery-focused individual-contributor role, centered on writing code, configuring infrastructure, reviewing pull requests, and resolving operational challenges rather than managing people or setting organization-wide strategy.

The role designs, builds, tests, deploys, monitors, and improves data pipelines and Azure platform infrastructure. It covers Azure services and infrastructure as code, data engineering with Databricks and Azure Data Factory, secure Azure networking, CI/CD, automated testing, software architecture, operational monitoring, and cost management. The engineer owns platform components and pipelines from design through production monitoring, incident response, and continuous improvement, and collaborates with data, analytics, data science, cloud, infrastructure, product, and business colleagues. The position also includes mentoring junior and mid-level engineers and applying generative AI tools in everyday engineering work.

The position is remote-friendly, with periodic travel for team meetings, onsite collaboration, or client engagements. Work is performed in a general office environment or from home, and occasional off-hours support may be needed for platform incidents or scheduled maintenance windows. The stated pay range is $101,600–$152,400, based on experience. Candidates must reside and be authorized to work in the United States.

Requirements

• At least 6 years of hands-on engineering experience, including meaningful experience in data engineering and cloud platform or infrastructure domains.
• At least 3 years working with Microsoft Azure services in production, including ADF, ADLS Gen2, Databricks, Azure Functions, Service Bus, Event Hub, and Azure Monitor.
• At least 2 years of hands-on Azure networking experience with VNets, NSGs, Private Endpoints, Private DNS, service endpoints, and firewall configurations.
• At least 2 years developing with Apache Spark and Databricks, including Delta Lake table design, schema evolution, and performance optimization.
• At least 4 years of production SQL development, including complex transformations, query tuning, indexing, and enterprise-scale data modeling.
• Strong Python development skills applied to data engineering, pipeline orchestration, or platform tooling.
• Demonstrated infrastructure-as-code experience; Terraform is preferred, while Bicep or ARM is acceptable.
• Hands-on experience building and maintaining Azure DevOps CI/CD pipelines; 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, including Azure AD, Managed Identities, RBAC, and Key Vault.
• Strong engineering fundamentals, including automated testing, code reviews, telemetry, iterative delivery, and DevOps.
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or equivalent practical experience.
• Must reside and be authorized to work in the United States.
• Must be inquisitive and open to innovation, including using AI to improve processes and patient and client experiences.

Nice To Haves

• Familiarity with data platform security and governance, including Unity Catalog, column-level security, data masking, and audit logging.
• Software engineering background in APIs, microservices, or distributed systems.
• Experience with polyglot storage architectures such as 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, such as feature stores, training data pipelines, or model-serving infrastructure.
• Familiarity with AKS, container networking, and Kubernetes-based workload deployment patterns.
• Relevant Azure certifications such as AZ-305, DP-203, or AZ-700.
• Familiarity with FinOps practices, Databricks cost management, and Azure cost-optimization tooling.

Responsibilities

• Deliver high-quality platform and data solutions that improve the reliability, speed, and accuracy of data.
• Use generative AI tools to accelerate development, improve code quality, troubleshoot systems, and design scalable solutions.
• Design, build, test, deploy, monitor, and improve data pipelines using Azure Data Factory, Databricks, Apache Spark, and Python.
• Implement Delta Lake patterns on Azure Data Lake Storage, 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.
• Implement data-quality monitoring such as row counts, schema validation, null checks, and freshness service-level agreements.
• Develop reusable pipeline templates and platform abstractions; translate business and product requirements into incremental, testable deliverables with clear acceptance criteria.
• Provision and manage Azure infrastructure using Terraform, Bicep, or ARM templates, keeping platform configuration version-controlled.
• Design and operate Azure 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.
• Implement observability through pipeline SLAs, performance dashboards, alerting, and cost tracking using Azure Monitor, Log Analytics, and Databricks system tables.
• Contribute to FinOps by monitoring compute costs, right-sizing clusters, configuring auto-termination, and flagging cost anomalies.
• Support containerized workloads running on Azure Kubernetes Service where required.
• Design and implement secure Azure networks using VNets, subnets, NSGs, Private Endpoints, Private DNS Zones, and service endpoints, minimizing unnecessary public internet exposure.
• Configure, troubleshoot, and document Private Link connectivity; diagnose DNS resolution and routing issues across Azure PaaS services.
• Apply encryption-in-transit and encryption-at-rest standards; maintain TLS configurations, key rotation, and secret-management practices; participate in security reviews and threat modeling.
• Partner with Cloud and Infrastructure teams on hub-and-spoke or landing-zone network topologies, and configure and validate firewall rules and IP allowlisting.
• Build and maintain Azure DevOps CI/CD pipelines to automate testing, validation, and deployment of data pipelines, notebooks, and infrastructure code.
• Follow and improve branching strategies, pull-request standards, code reviews, and engineering workflows.
• Write unit, integration, and data-quality tests as standard deliverables.
• Contribute to engineering standards and pattern libraries to promote consistency and ease onboarding.
• Write maintainable Python and SQL using appropriate design patterns, modular decomposition, and API design principles.
• Participate in design and architecture discussions, conduct code and design reviews, and address technical debt incrementally.
• Collaborate with data engineering, analytics, data science, and cloud/infrastructure peers to deliver integrated platform solutions.
• Mentor junior and mid-level engineers through code reviews, pair programming, and technical guidance.
• Explain platform capabilities, limitations, and trade-offs clearly to product and business stakeholders.
• Provide occasional off-hours support for platform incidents or scheduled maintenance windows.

Benefits

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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior