Database Platform Distinguished Engineer

Dayforce

1d•$140,900 - $251,600•Remote

About The Position

We are redefining the data foundation that powers Dayforce. As a Distinguished Database Platform Engineer, you will set the technical direction for how we design, scale, and operate our data platforms—spanning transactional systems and modern lakehouse architectures. This is a hands-on architectural role for a technical leader who thrives on solving complex data challenges, influencing engineering at scale, and modernizing data platform engineering through cloud, automation, and AI.

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

Nice To Haves

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

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