Position – Data & Backend Architect – Azure Data Brick, Data Layer (Claude AI–Driven)
Experience: 15+ years of software engineering experience, including 5+ years
Location: New York OR New Jersey – Remote (but travel when required)
Data & Backend Architect – Azure Data Brick, Data Layer (Claude AI–Driven)
Product Development, Sustenance, Modernization & Agentic AI infusion
Travel: 25% during active client engagements
Experience Level: 15+ years
About Persistent Systems:
Persistent Systems is a global digital engineering and enterprise modernization partner. We combine agentic AI, proprietary accelerators, and a forward-deployed delivery model to help PE-backed software companies, regulated enterprises, and Global Capability Centers modernize legacy systems and embed AI at the core of how they build and operate software.
About the Role:
· As a Data & Backend Architect, you will be the senior-most hands-on backend engineer embedded within the client platform team, responsible for architecting and delivering the core backend systems that power cross-portfolio data normalization, reporting, and advanced analytics.
· In this role, you will leverage Claude AI extensively as an engineering productivity accelerator—driving faster GTM, improving development velocity, and enabling high-quality code, design, and delivery outcomes. Claude will be a core part of your daily engineering workflow (coding, debugging, system design, documentation, and acceleration of delivery), but not a runtime dependency of the platform architecture.
· This is a pure individual contributor architect role with end-to-end ownership of backend architecture and engineering delivery. Approximately 70–75% of your time will be hands-on coding, system design, and backend engineering, with the remainder focused on collaboration with product and client stakeholders
Key Responsibilities:
· Architect and build the core backend systems that power cross-portfolio data normalization, scalable reporting layers, and analytics-ready data platforms.
· Design and implement backend services, APIs, and data pipelines using an Azure-based stack (Azure Web Apps, Microsoft Fabric), ensuring high performance, scalability, and production readiness.
· Structure and deliver data models and transformation pipelines that standardize disparate portfolio company data into a consistent, queryable format for dashboards and downstream analytics
· Enable natural-language and ad hoc analytics capabilities by building backend systems that support AI-driven querying over normalized enterprise data.
· Leverage Claude AI extensively as an engineering productivity accelerator—driving faster GTM through rapid prototyping, code generation, debugging, and design exploration across the development lifecycle.
· Establish and scale Claude-driven development practices to improve engineering velocity, reduce cycle times, and enhance code quality and consistency within the embedded team.
· Own backend technical design for platform evolution, translating product requirements into robust, scalable backend implementations in close collaboration with the client$B!G(Js product team.
· Operate as a fully embedded engineer within the client team, contributing to day-to-day development, design reviews, and delivery workflows aligned to a dedicated, full-time engagement model.
· Maintain high engineering standards including code quality, testing rigor, modular architecture, and maintainability across all backend deliverables.
· Drive execution discipline and delivery outcomes, ensuring backend systems are production-grade, aligned with roadmap timelines, and optimized for rapid iteration enabled by Claude AI.
Required Qualifications:
· 15+ years of software engineering experience, including 5+ years at Principal Architect / Senior IC level building large-scale backend and data platforms in enterprise environments.
· Proven experience designing and delivering data-intensive backend systems that support reporting, analytics, and multi-source data normalization at enterprise scale.
· Demonstrated ownership of backend architecture and delivery for at least two large platform programs with measurable outcomes (scalability, performance, usability, or time-to-market improvements).
· Active hands-on coder, currently writing production-grade backend code, reviewing pull requests, and driving reference implementations.
· Strong experience working in embedded/forward-deployed engineering models, collaborating directly with product teams and stakeholders to translate evolving requirements into backend systems
· Extensive usage of Claude AI or equivalent AI coding assistants as a core development accelerator—demonstrated impact on engineering velocity, code quality, and GTM timelines.
Backend & Data Platform Engineering (Required — Primary Focus Area)
· Strong expertise in backend development using modern service-oriented and API-driven architectures (REST, gRPC, event-driven patterns).
· Experience designing data ingestion, transformation, and normalization pipelines for heterogeneous enterprise data sources.
· Deep understanding of scalable data modeling for reporting, dashboards, and analytics consumption layers.
· Proven ability to build backend systems that enable ad hoc querying and analytics over structured datasets.
· Expertise in distributed systems design, including fault tolerance, performance optimization, and scalability patterns.
Cloud & Azure Stack (Required — Primary Focus Area)
· Hands-on experience with Azure-based backend systems, including App Services / Web Apps and cloud-native service design.
· Experience working with modern cloud data platforms, including Microsoft Fabric or equivalent (data lake, warehouse, transformation pipelines).
· Familiarity with building backend systems that integrate with AI and analytics layers, supporting natural-language or advanced querying use cases.
· Strong understanding of cloud-native observability, deployment patterns, and performance tuning.
Claude AI–Driven Engineering (Required — Differentiator)
· Extensive hands-on usage of Claude AI for software development, including:
· Code generation and rapid prototyping
· Debugging and optimization
· System design exploration
· Documentation and knowledge capture
· Demonstrated ability to accelerate GTM timelines using Claude AI, reducing development cycle times while maintaining high quality.
· Experience establishing Claude-driven development workflows and best practices within engineering teams.
· Ability to balance AI-assisted development with strong engineering judgment, ensuring maintainable, production-grade code.
Engineering Excellence & Delivery (Required):
· Strong grounding in engineering best practices: code quality, modular architecture, testing discipline, and maintainability
· Experience delivering in time & materials or roadmap-driven engagements, adapting to evolving scope and priorities
· Excellent problem-solving and system design skills, with the ability to operate independently in high-ownership IC roles
· Strong communication skills, including working with product managers and stakeholders to shape technical solutions
Microsoft Fabric & Analytics Layer (Required):
Experience with Microsoft Fabric (OneLake, Lakehouse, Warehouse, data pipelines) for building analytics-ready platforms
Understanding of reporting and dashboarding ecosystems (e.g., Power BI or equivalent)
Awareness of designing data platforms optimized for downstream analytics and ad hoc insights generation
• Preferred Qualifications Microsoft certifications relevant to data and cloud platforms: Azure Solutions Architect Expert, Azure Data Engineer Associate, Azure AI Engineer Associate, Microsoft Fabric Analytics Engineer or equivalent.
• Demonstrated use of Claude AI (or equivalent AI coding assistants) to accelerate software delivery, with proven impact on reducing development cycle times and improving engineering productivity.
• Contributions to the engineering community, such as conference speaking, open-source contributions, or technical writing in backend systems, data platforms, or AI-enabled development practices.
• Industry experience in one or more of the following domains: Private Equity portfolio platforms, financial services, enterprise SaaS, or data-driven digital products.
• Experience working on data platform initiatives for multi-entity or portfolio-based organizations, including standardization and normalization of distributed data sources.
• Exposure to analytics-driven product platforms, including systems powering dashboards, reporting, and ad hoc insights generation.
• Experience operating in high-velocity, embedded delivery models, including partnerships with product teams, evolving roadmaps, and rapid GTM expectations.
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