Product Software Engineer

Wolters Kluwer•Coppell, TX

3d•$74,700 - $127,950•Onsite

About The Position

Wolters Kluwer Tax & Accounting is seeking a Software Engineer, Data Workflow Automation, to design, build, and maintain resilient systems responsible for processing large volumes of customer data, documents, and transactions. This role focuses on engineering reliable workflow solutions that ingest, validate, transform, and export information across desktop applications, cloud services, APIs, databases, and file-based systems. Role Overview Design automation systems that function like an automated logistics center, reliably receiving, processing, transforming, and delivering thousands of files and transactions daily. Build fault-tolerant, self-healing workflow platforms that execute in distributed Windows-based cloud environments. Drive engineering excellence, resiliency, operational scalability, and maintainable software design.

Requirements

Bachelor degree in Computer Science, Software Engineering, Information Systems, or equivalent practical experience.
5+ years of professional software engineering experience.
Strong experience developing applications using C#, .NET Framework, .NET Core, and modern .NET platforms.
Experience designing workflow automation, process orchestration, or systems integration solutions.
Strong understanding of object-oriented design and software engineering principles including SOLID, DRY, Clean Code, and design patterns.
Strong SQL and data analysis skills.
Experience working with Azure cloud services and distributed application architectures.
Experience building enterprise workflow automation solutions that process large volumes of customer files and transactions.
Experience designing automation that operates reliably within Windows-based virtual machine environments and unattended execution scenarios.
Experience building systems that support bulk file ingestion, processing, transformation, and export workflows.
Understanding of ETL and ELT methodologies including data mapping, transformation, validation, reconciliation, and migration processes.
Experience with queue-based architectures, event-driven systems, asynchronous processing, and distributed workloads.
Experience automating Windows desktop applications running in unattended or headless execution environments.
Experience interacting with file systems, background processes, services, application interfaces, and system IO.
Ability to develop robust abstraction layers that tolerate application evolution and configuration changes.
Experience with virtualized Windows environments and cloud-hosted worker infrastructure.
SOLID design principles.
DRY methodologies.
Clean Code practices.
Dependency Injection patterns.
Unit testing and automated validation strategies.
Continuous Integration and Continuous Delivery (CI/CD).
Observability and production monitoring practices.
Design systems that fail gracefully.
Recover automatically.
Support checkpoint-based recovery.
Preserve transactional integrity.
Provide actionable telemetry and logging.
Operate reliably under sustained high-volume processing conditions.
Familiarity with Agentic SDLC practices and emerging AI-assisted engineering workflows.
Experience utilizing Specification Driven Development (SDD) approaches and understanding both benefits and limitations.
Ability to apply engineering judgment when leveraging AI-assisted development tools

Responsibilities

Design, develop, and maintain large-scale workflow automation platforms that process high volumes of files, documents, and business transactions.
Build resilient software systems that ingest, validate, transform, enrich, and export data across multiple internal and external systems.
Engineer fault-tolerant solutions capable of detecting failures, recovering automatically, and minimizing operational intervention.
Develop automation frameworks that interact with Windows desktop applications, cloud services, databases, APIs, file systems, and third-party platforms.
Design and implement workflow orchestration, checkpointing, retry strategies, state management, and recovery mechanisms.
Support and modernize existing applications by leveraging legacy MVC implementations while developing and integrating modern RESTful and GraphQL interfaces.
Develop solutions that operate within distributed cloud-hosted virtual machine environments and support large-scale concurrent processing workloads.
Create telemetry, monitoring, logging, and diagnostic capabilities.
Leverage modern AI-assisted development workflows where appropriate.