Application Architect

Application architecture and design

•       Define target-state application architectures across front end, mobile, APIs and services, integration, application data stores, and cloud infrastructure.

•       Assess applications already in development, name the decisions that are still open, and steer them to the target state without interrupting delivery.

•       Choose architecture styles that fit the problem: modular monolith, microservices, event-driven, or serverless.

•       Design domain APIs and event contracts, including API gateway, versioning, and asynchronous messaging patterns.

•       Write architecture decision records (ADRs), reference architectures, and roadmaps that engineering teams build against.

Data-driven applications

•       Design applications that treat a governed lakehouse Gold layer as the system of record. Know the split between analytical serving (Delta tables, Databricks SQL) and operational serving (Azure SQL, Cosmos DB), including change data capture feedback loops and eventual consistency.

•       Pick the right serving store per use case: relational for transactions, NoSQL for low-latency reads, analytical stores for reporting. Present each option with its run cost and operating burden, and choose the smallest footprint that meets the need.

•       Work with data architects and modelers on master data, golden records, and the contracts that keep applications decoupled from platform internals: versioned Gold schemas, schema evolution, master identifiers, and how an application shows current versus point-in-time history (SCD Type 2) and handles golden-record merges.

•       Design applications as good citizens of the data platform: emit clean, well-keyed operational data for change data capture, take reference data from the curated layer instead of forking it, and manage schema changes to operational stores with the ingestion pipelines in mind.Design embedded analytics and AI features, including how models are called and monitored from applications.

Legacy modernization

•       Assess legacy applications: code, dependencies, data access, performance, and integration points.

•       Pick a strategy per application (rehost, re-platform, re-architect, or retire) and sequence the work to limit business risk.

•       Design hybrid and transitional architectures, such as the strangler fig pattern, so old and new systems run side by side until cutover.

Security, compliance, and engineering standards

•       Build in identity, role-based access, secrets management, and encryption from the first design.

•       Design for regulated data, including PII and health information, in line with each client's compliance regime.

•       Set standards for CI/CD, containers, infrastructure as code, observability, and automated testing.

Technical leadership and client engagement

•       Lead design reviews and set coding and API standards for client and Aubrant engineering teams.

•       Co-author design decisions with the client's engineers and record them as ADRs in the client's own repositories and backlog, so every decision is traceable and nothing is delivered that the client team did not take part in.Mentor senior engineers on architecture patterns and cloud practices.

•       Build proofs of concept that test risky decisions before full development starts.

•       Present options and recommendations to client technology leaders, and support Advisory on pre-sales solutioning and estimates.

•       Add the patterns you build to the Studio's shared catalog so the next engagement starts further ahead.

•       Bachelor's degree in computer science, software engineering, or a related field, or equivalent experience.

•       Professional working proficiency in written and spoken English.

•       10+ years of professional software engineering, with at least 5 years as a solutions or application architect.

•       Full-stack architecture experience: modern front ends (React, Angular, or similar), mobile apps, RESTful APIs, microservices, and event-driven systems.

•       Hands-on depth in at least one enterprise stack, with .NET (C#, ASP.NET Core) strongly preferred. Java, Node.js, or Python experience is a plus.

•       Deep Microsoft Azure experience: App Service, Azure Kubernetes Service (AKS), Azure Functions, API Management, Event Grid or Service Bus, Azure SQL, Cosmos DB, and Entra ID.

•       Experience building applications on a lakehouse data platform (Delta Lake or Iceberg, medallion tiers, change data capture, master data management), including serving stores and APIs over curated Gold data.A record of modernizing legacy applications, including .NET Framework or Web Forms, with patterns such as strangler fig and phased re-platforming.

•       Hybrid architecture across cloud and on-premises: identity federation, data synchronization, and network connectivity.

•       Security architecture: zero trust, identity and access management, encryption, and handling PII in regulated settings.

•       Working knowledge of CI/CD, containers, and infrastructure as code (Terraform, Bicep, or ARM templates).

•       Performance and observability: load testing, caching, capacity planning, and Application Insights or equivalent.

•       Clear communicator with executives and engineers alike. Aubrant is a client-facing consultancy, and you will work directly with client leadership.

•       Able to run two or three engagements at once and stay effective when requirements are unclear.

•       Experience joining engagements already in progress and advising an in-house engineering team part-time.

•       Domain modeling: domain-driven design, bounded contexts, and mapping an application's domain model to a canonical enterprise model before committing to tables or APIs.

•       Working knowledge of lakehouse and data platform concepts (Delta Lake or Iceberg, medallion tiers, change data capture, master data management) is a plus.

•       Experience with Azure Databricks, Azure Synapse, Microsoft Fabric, or Microsoft Purview from the application side is a plus.

•       Experience building AI-enabled applications, such as calling and monitoring ML models (MLflow or Azure Machine Learning) and retrieval-augmented generation, is a plus.

•       Working experience on AWS or Google Cloud in addition to Azure is a plus.

•       Experience with IoT, telematics, or other high-volume event and streaming data is a plus.

•       Experience in regulated industries such as healthcare, life sciences, financial services, logistics, or the public sector, including HIPAA, SOC 2, or PCI DSS, is a plus.

•       Power BI embedded analytics and row-level security experience is a plus.

•       Experience using AI coding tools within a governed software delivery process, with human review and decisions the client can trace, is a plus.

•       Azure certifications, such as Azure Solutions Architect Expert or Azure Developer Associate, are a plus.