Software Developer Sr

Dayforce; Toronto; Hybrid; CAD 110,000 - 180,000; Full time

Job summary

Dayforce is seeking a software engineer to join the Data Platform team. You will design and develop cloud-native services, APIs, and framework components powering analytics, AI, and customer-facing data products.

You’ll work with Python, C#, and Azure-based tech such as Databricks and Delta Lake, delivering production-quality services and scalable pipelines. You will collaborate with data scientists and product teams to ensure secure, high-performance data solutions, while upholding CI/CD and

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• 5+ years of professional software development experience.
• Experience with C#/.NET and Python for backend services.
• Experience designing and building REST APIs and distributed backend services.
• Experience building cloud-native data platforms on Microsoft Azure.

Responsibilities

• Design and develop production software in Python and C# that powers the data platform.
• Develop reusable platform libraries, frameworks, and SDKs used by other engineering teams.
• Design, build, and maintain REST APIs and backend services powering data products.
• Own software components from design through deployment, monitoring, and ongoing operational support.
• Build and operate production services with reliability, observability, performance, and scalability in mind.
• Participate in architecture discussions and improve the platform through automation and best practices.
• Apply CI/CD, automated testing, and clean architecture principles.
• Build scalable ingestion services and data processing frameworks for analytics and AI needs.
• Collaborate with Data Scientists to support AI agents and data-driven features.

Skills

C#/.NET

Python

REST APIs

Distributed systems

Azure

Databricks

Azure Data Lake Storage

SQL

CI/CD

Dev tooling

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

Terraform

Azure DevOps

Git

Job description

About the Opportunity

The Dayforce Data Platform team is building the next generation of our enterprise data platform. We are looking for a software developer who enjoys building services, APIs, frameworks, and core platform components that power our enterprise data platform. This is a software engineering role focused on platform engineering, reusable systems, developer tooling, and cloud-native services that enable analytics, AI, and customer-facing products.

In this role, you will design and develop the software components that power our cloud-native data platform, including ingestion services, processing frameworks, APIs, and orchestration. You'll write production software in Python and C#, build APIs, and develop scalable data services alongside modern data platform components. Success comes from building production-quality services, APIs, frameworks, and platform capabilities that enable data products, analytics, and AI at scale.

You will work closely with software engineers, data scientists, product managers, and analytics teams to build data services that are performant, secure, and scalable. This is an opportunity to influence the architecture of a modern SaaS data platform, designing distributed systems that process large-scale data while exposing reliable APIs and services to engineering teams and customer-facing applications. You'll work with technologies including Databricks, Apache Spark, Delta Lake, Azure Data Lake Storage, SQL Warehouse, and cloud-native Azure services.

If you're passionate about software engineering, distributed systems, cloud-native platforms, and building the infrastructure that powers data-driven products, we'd love to hear from you.

What You'll Get to Do

• Design and develop production software in Python and C# that powers the data platform.
• Develop reusable platform libraries, frameworks, and SDKs used by other engineering teams.
• Design, build, and maintain REST APIs and backend services that power internal and customer-facing data products.
• Own software components from design through deployment, monitoring, and ongoing operational support.
• Build and operate production services with a focus on reliability, observability, performance, and scalability.
• Participate in architecture discussions and continuously improve the platform through automation and engineering best practices.
• Apply software engineering best practices, including code reviews, automated testing, CI/CD, and clean architecture.
• Build scalable ingestion services, processing frameworks, and reusable data platform components.
• Develop reliable pipelines using Azure Data Lake Storage, Databricks, and SQL Warehouse to support analytics, reporting, machine learning, and customer-facing data products.
• Develop metadata-driven data processing frameworks that improve automation and reusability.
• Partner with Data Scientists to support AI agents.
• Optimize pipeline performance, storage, and compute costs across Azure and Databricks.
• Contribute to data governance initiatives, including lineage, metadata management, documentation, and data quality standards.
• Support de-identification and privacy requirements for customer data across multiple regions.
• Collaborate with Product Management, Engineering, Analytics, and Data Science teams to deliver high-quality data solutions.

Skills and Experience We Value

• 5+ years of professional software development experience, preferably building cloud-native backend systems or data platforms.
• Strong software development experience with C#/.NET and Python.
• Experience designing and building REST APIs and distributed backend services.
• Experience designing maintainable, testable software using modern software engineering principles.
• Experience building distributed backend services or microservices.
• Experience with automated testing, code reviews, CI/CD, and production operations.
• Experience designing public or internal APIs.
• Experience building cloud-native data platforms on Microsoft Azure.
• Experience designing, debugging, and operating distributed systems in production.
• Strong problem-solving and troubleshooting skills for distributed data processing systems.
• Strong SQL skills with experience designing high-performance analytical data models.
• Experience building pipelines using Databricks, Azure Data Factory, or similar technologies.
• Experience working with Azure Data Lake Storage and modern lakehouse architecture.
• Experience building solutions for enterprise SaaS or multi-tenant applications.
• Excellent communication and collaboration skills.
• Experience supporting developers to integrate data platform components into end-user applications.
• Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.

What Would Make You Stand Out

• Experience with containerized applications (Docker/Kubernetes).
• Experience creating compilers for domain-specific languages.
• Experience with event-driven architectures (Kafka, Event Hub, or Azure Service Bus).
• Experience supporting globally distributed SaaS platforms.
• Experience with data privacy, masking, and de-identification techniques.
• Experience monitoring production data platforms using Azure Monitor, Log Analytics, or Databricks monitoring tools.
• Experience with Infrastructure as Code (Terraform, Bicep, or ARM).