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Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region. Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce. Our brand promise - Makes Work Life Better™ - Reflects our commitment to employees, customers, partners and communities globally. 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). What’s In It For You Dayforce is fueled by the diversity of our talented employees. We are an equal opportunity employer and consider and embrace ALL individuals and what makes them unique. We believe our employees should be happy and healthy, with peace of mind and a sense of fulfillment. We encourage individuals to apply based on their passions. Dayforce employees and their families are eligible to participate in the following benefits programs: medical, dental, vison, and life insurance. Dayforce employees are also eligible to participate in a 401k plan (plus match) and a Global Employee Stock Purchase Plan. Employees also receive unlimited Time Away From Work (in lieu of accrued vacation time), 10 paid US holidays, up to 80 hours of paid sick time and 17 weeks of paid parental leave, subject to the terms of the applicable policy or program. With a commitment to community impact, including volunteer days and our charity, Dayforce Cares we provide opportunities for you to thrive both in your career and personal life. Our focus is not just on your job but on supporting you to be the best version of yourself. About The Salary Ranges Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate’s experience, skills, budget and location. Our company is committed to providing a fair, equitable, and competitive package that reflects the value an individual brings to the organization. Fraudulent Recruiting Beware of fraudulent recruiting. Legitimate Dayforce contacts will use an @dayforce.com email address. We do not request money, checks, equipment orders, or sensitive personal data during the recruitment process. If you have been asked for any of the above, or believe you have been contacted by someone posing as a Dayforce employee, please refer to our fraudulent recruiting statement found here: https://www.dayforce.com/be-aware-of-recruiting-fraud Dayforce actively monitors all job applic
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In your interview, expect this: 'Walk me through the last time you had to debug something that took you more than an hour. What was it, what did you try first, and what would you do differently?' Hiring managers ask this to see if you think systematically or just try random fixes. Have a real example ready with specifics.