Database Platform Distinguished Engineer

Dayforce is a global human capital management company headquartered in Toronto and Minneapolis. They are seeking a Distinguished Database Platform Engineer to lead the design and operation of scalable data platforms, focusing on both transactional and analytical systems while modernizing data platform engineering through cloud and automation.

Responsibilities:

• Define and drive the architecture of highly scalable, resilient data platforms across OLTP and analytical systems
• Lead the evolution of Lakehouse architecture, supporting unified data and analytics
• Own performance, reliability, and scalability across critical database platforms through deep, hands-on expertise
• Guide adoption of modern platforms and tooling (e.g., Databricks, cloud-native services, automation frameworks)
• Partner with engineering and data teams to shape data models, access patterns, and platform capabilities
• Influence technical strategy and raise engineering standards across the organization
• Lead hands-on investigation and resolution of complex customer database and data lake performance, reliability, and data consistency issues, including direct analysis of production systems when needed

Requirements:

• Expert-level experience with large-scale database platforms (e.g., SQL Server, PostgreSQL) in production environments
• Strong background in modern data architecture and distributed data systems
• Experience with Databricks and cloud data platforms (AWS, Azure, or GCP)
• Familiarity with both relational and NoSQL systems (e.g., MongoDB)
• Deep expertise in performance tuning, scalability, and high-availability design
• Proven ability to operate as a technical leader—setting direction while remaining hands-on
• Comfort leveraging AI and automation to improve database platform operations and engineering productivity
• 10+ years of experience designing, operating, and optimizing large-scale production database platforms
• Deep hands-on expertise with enterprise relational database technologies such as Microsoft SQL Server and PostgreSQL
• Strong experience with distributed data systems and modern data architectures, including Data Lake, Delta Lake, or Lakehouse platforms
• Experience troubleshooting complex database performance, scalability, reliability, and data consistency issues in production environments
• Experience with cloud platforms and cloud-native data services (AWS, Azure, or GCP)
• Strong understanding of high availability, disaster recovery, backup/recovery, indexing, query optimization, performance tuning, Change Data Capture, and Event Driven systems
• Experience working with automation, observability, and infrastructure-as-code approaches for platform operations
• Proven ability to influence technical direction and collaborate effectively across engineering, infrastructure, and data teams
• Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience
• Experience with Databricks and modern Lakehouse implementations supporting unified analytics and operational workloads
• Experience with NoSQL technologies such as MongoDB or other distributed document/key-value databases
• Experience designing and operating platforms that support both transactional and analytical workloads at enterprise scale
• Experience modernizing legacy database environments into cloud-native or hybrid architectures
• Demonstrated technical leadership in architecting shared platform capabilities, standards, and engineering best practices
• Experience leveraging AI-assisted tooling or automation to improve operational efficiency, troubleshooting, and engineering productivity
• Experience mentoring senior engineers and leading cross-functional technical initiatives
• Experience designing secure data platforms with strong governance and access-control models
• Familiarity with compliance frameworks and data residency requirements (SOC2, GDPR, HIPAA, etc.)
• Expertise with encryption, secrets management, auditing, and zero-trust approaches
• Advanced cloud, database, or data engineering certifications are considered an asset
• Experience in large-scale SaaS, HCM, fintech, or other highly regulated enterprise software environments is an asset