Role Description Provide dedicated, long‑term engineering ownership of core Quadient and Groovy‑based processing, onboarding workflows, and shared communication components. Act as a persistent platform capability enabling scalable onboarding and consistent communications delivery across the enterprise. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. as you take on some tough challenges. Primary Responsibilities: - Develop, enhance, and maintain Groovy scripts, Quadient business logic, templates, and shared data‑alignment components used across CCM compositions. - Support onboarding workflows by configuring communication setups, data mappings, template builds, and application of standardized composition patterns. - Partner with TPOs, business stakeholders, and implementation teams to translate requirements into reusable, scalable technical solutions. - Support production readiness by assisting with communication reviews, approvals, and readiness validation. - Troubleshoot communication build issues, routing and orchestration logic defects, variance detection failures, and batch/job‑processing problems. - Serve as a floating technical resource to support and train new onboarding teams as they come online (tools, processes, template operations). - Contribute to ongoing documentation, playbook refinement, and continuous improvement initiatives to strengthen platform stability and reuse. - Design, develop, and deploy AI-powered solutions to address complex business challenges with emphasis on responsible use of AI. Qualifications - 3+ years of experience in developing and maintaining Groovy scripts, Quadient business rules, templates, and shared components. Requirements - Undergraduate degree or equivalent experience. - 5+ years of hands-on experience using the Quadient Suite of tools (e.g., Quadient Inspire, Interactive, Scaler) in an enterprise CCM environment. - Proven experience supporting end-to-end communication onboarding, including data mappings, template configuration, and application of standardized composition patterns. - Experience troubleshooting CCM build issues, routing/orchestration logic, variance detection, and batch or job-processing failures. - Demonstrated ability to translate business and technical requirements into reusable, scalable platform solutions. - Experience working closely with Product Owners/TPOs, business stakeholders, and implementation teams in an Agile or hybrid delivery model. - Familiarity with production readiness processes, communication reviews, approvals, and release validation. - Experience supporting or mentoring onboarding teams and contributing to platform documentation, playbooks, and continuous improvement initiatives. Benefits - Comprehensive benefits package. - Incentive and recognition programs. - Equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). - Salary range from $91,700 to $163,700 annually based on full-time employment.

Role Description 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. - 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 Qualifications - 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 Requirements - 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 Benefits - Medical, dental, vision, and life insurance - 401k plan (plus match) - Global Employee Stock Purchase Plan - Unlimited Time Away From Work (in lieu of accrued vacation time) - 10 paid US holidays - Up to 80 hours of paid sick time - 17 weeks of paid parental leave, subject to the terms of the applicable policy or program - Opportunities for community impact, including volunteer days and charity initiatives

• Help design, support, and evolve the data infrastructure for environmental research. • Work closely with federal stakeholders and technical teams to translate data orchestration needs. • Manage PostgreSQL databases, optimize SQL based workflows, and support Python driven automation and CI/CD pipelines. • Contribute to improving observability, reliability, and operational performance across data pipelines. • Help engineer the platform that keeps high value environmental data moving, accessible, and trusted.

• Execute and extend the engineering patterns established by the Snowflake Platform Lead and Senior Data Platform Engineer. • Responsible for the day-to-day build, deployment, and operation of Snowflake objects, pipelines, and tooling. • Own Implementation of Snowflake objects and roles in Terraform per established patterns. • Day-to-day operation of CI/CD pipelines for database changes. • Configuration and maintenance of assigned ingestion pipelines (Snowpipe, Streams/Tasks, managed connectors). • First-line response to platform alerts on assigned components. • Documentation and runbook updates for work this role delivers. • Contributes to Architecture and pattern design decisions.