• Collaborate with business stakeholders to gather and document requirements for prioritized data domains • Profile data and analyze source systems and data structures to assess content, quality, and structure • Develop comprehensive data mapping documents, including source-to-target specifications and transformation logic • Work with Master Data Management (MDM) and integration teams to validate mappings and ensure alignment with enterprise data models • Support workshops and working sessions to refine business rules, data definitions, and domain onboarding plans • Assist in identifying data quality issues and contribute to metadata and lineage documentation • Create and maintain data catalogs to ensure consistent documentation, easy discovery, and effective management of enterprise data assets • Coordinate with platform subject matter experts (SMEs) to ensure mappings are compatible with MDM, data hub, and integration platform configurations • Track mapping progress, dependencies, and issues across teams and tools, providing timely updates and resolving blockers • Collaborate with business stakeholders and project teams to understand data requirements for HR, Finance, Legal, and Professional Services functions • Analyze and document existing data sources, structures, and business rules within legacy systems • Develop data mapping specifications to ensure accurate migration to new systems • Support the extraction, transformation, and loading (ETL) of data, including profiling, cleansing, and validating migrated data • Perform data quality assessments and implement data validation processes to ensure completeness and accuracy • Assist in designing and testing data integrations between new enterprise platforms and other business applications • Create and maintain comprehensive documentation of data models, flows, and transformation rules • Identify and resolve data-related issues during migration and post-implementation • Provide regular updates and insights to project leaders and stakeholders regarding data migration progress and risks • Support ongoing data governance and quality initiatives as new systems are adopted

Role Description As an Intern at Dayforce, you’ll gain real-world experience with meaningful responsibilities, access to development programs, and the chance to collaborate globally, bringing new ideas and optimizing processes across multiple business units. Data analysts are responsible for evaluating data to develop reports and visualizations that identify trends or analytics that help companies make better-informed business decisions. They are comfortable working with structured data, performing analytics, building appropriate visualizations, and drawing conclusions based on empirical evidence rather than gut feel. They are good communicators who can translate their findings into business-friendly language. What you’ll get to do: - Develop reports and visualizations from structured data using Power BI - Prepare datasets by writing scripts in SQL or Python (must be able to do table joins) - Create standard measures to help our clients understand the health and efficiency of their organization. Examples of measures include: Quality of Hire, Turnover, Absenteeism Rate - Create research questions, conduct quantitative data analysis, and communicate findings to others including media and academic partners - Create blog posts to be published on Dayforce’s blog Qualifications - Currently pursuing a Bachelor’s degree, Master’s degree, or Post-Graduate Certificate in Data Analytics, Data Science, Statistics, Business Analytics, Computer Science, Economics, Psychology, Industrial-Organizational Psychology, or a related quantitative field. - Knowledge of human resources processes and procedures - Knowledge of people analytics best practices - SQL - Data management - Power BI - Strong verbal and written communicator - Strong organizational skills - Attention to detail - Learning mindset - Curiosity - Ability to interpret statistics Requirements - Full-time availability of 37.5 – 40 hours weekly is required to be eligible for this opportunity. Benefits - Experience working for one of the fastest growing Human Capital Management technology companies in the world - Access to Dayforce’s development programs and resources - Ability to work with as well as create relationships with members across the globe - Autonomy to bring forth new ideas and optimize existing structures within the organization - Meaningful responsibilities, enabling you to obtain ‘real-world’ experience - Dynamic hands-on exposure to multiple business-units and stakeholders across Dayforce

• Define and lead the Data & Analytics Practice vision, growth strategy, and multi-year roadmap • Drive evolution from traditional data warehousing to: Modern data platforms (lakehouse, real-time, domain-oriented architectures) • AI-enabled data ecosystems built for production-grade analytics and AI workloads • AI-enabled data products that deliver governed, reusable, and business-aligned data assets at scale • Establish standards and best practices across data engineering, modeling, architecture, governance, quality, and lifecycle management • Shape how the Practice differentiates in the market through offerings, accelerators, and delivery models • Act as the Practice's executive voice internally — influencing investment decisions, headcount plans, and strategic priorities • Provide active oversight and quality assurance on key client engagements, ensuring: Strong architecture, scalability, and alignment to client business outcomes • Consistency in delivery approach, data product thinking, and engineering quality • Build and scale reusable delivery accelerators, including: Ingestion frameworks for batch, real-time, and event-driven pipelines • Data quality and observability toolkits • Reusable data products: curated datasets, semantic models, and feature-ready datasets • Standardized data models and transformation pipelines • Drive adoption of data-as-a-product principles across client engagements: Clear ownership, SLAs, and lifecycle management • Discoverability through catalogs and semantic layers aligned to client business domains • Improve delivery velocity through standardization, reuse, and AI-assisted data engineering practices and AI-enabled accelerators • Serve as an escalation point and trusted advisor on complex client situations • Drive adoption of AI across the data lifecycle in client engagements, including: Data discovery, profiling, and quality automation • Metadata management and semantic layer evolution • Intelligent pipelines and data observability • Partner with our Product Engineering Capability to ensure: Client data platforms reliably support AI/ML and GenAI use cases • Strong architectural alignment between data foundations and application-layer AI capabilities • Develop reusable patterns for feature engineering, ML-ready datasets, and data pipelines supporting AI-driven use cases in client environments • Serve as Presidio Digital's external voice for Data & Analytics — in client conversations, industry forums, and the broader market • Develop and drive thought leadership, POVs, and go-to-market narratives on: Modern data platforms and cloud-native architectures • Data-as-a-product and AI-enabled data ecosystems • Enable internal teams (Sales, Presales, Delivery) with playbooks, collateral, storytelling, and training • Partner with Sales and Presales to shape data-led transformation opportunities and support strategic pursuits • Define and package client-facing service offerings, including: Data platform modernization • Data foundation for AI • Analytics transformation and data product adoption • Actively contribute to pipeline growth in key accounts through proactive opportunity identification and solution shaping • Develop proposals, delivery models, and value propositions that are competitive and client-outcome-driven • Build and mentor a high-performing Data & Analytics team — hiring, developing, and retaining top talent across data engineering, data architecture, and analytics engineering

• Assess research feasibility and translate clinical questions into analytic plans • Extract, validate, and manage data from Epic, Databricks, and other sources • Perform data cleaning, quality assurance, and statistical analyses • Support IRB submissions and ensure compliance with data governance standards • Generate tables, figures, and visualizations for manuscripts and presentations • Collaborate with investigators on interpretation, abstracts, and dissemination