Data & Backend Architect – Azure Data Brick, Data Layer (Claude AI–Driven)

Position –    Data & Backend Architect – Azure Data Brick, Data Layer (Claude AI–Driven) 

Experience: 15+ years of software engineering experience, including 5+ years at Principal Architect / Senior IC level

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.
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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.
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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.
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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.
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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.
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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
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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.