Job Description

Job Description

Job Description

Description:

Why Work at Paylocity

Paylocity is an award-winning provider of cloud-based HR and payroll software solutions, offering the most complete platform for the modern workforce. The company has become one of the fastest-growing HCM software providers worldwide by offering an intuitive, easy-to-use product suite that helps businesses automate and streamline HR and payroll processes, attract and retain talent, and build a strong workplace culture.

While traditional HR and payroll providers automate basic HR processes such as payroll and benefits administration, Paylocity goes further by developing tools that HR and businesses need to compete for talent and deliver against the expectations of the modern workforce.

Many companies offer payroll and human capital management (HCM) solutions, but Paylocity takes technology to the next level. We’ve evolved beyond HCM to a next generation employee experience platform. With uniquely designed solutions that help companies engage employees, we’ve changed how and where work gets done and created a more personalized work environment.

At Paylocity, people matter most and have always been at the heart of our business. As an intern, you’ll be supported through mentorship, hands-on learning, and meaningful work that helps you grow your technical and professional skills while contributing to real products used by thousands of customers. Join Paylocity as we continue to transform the future of technology.

Product & Technology at Paylocity

Help enhance communication and enable employees to connect, collaborate, and create from anywhere with a position in Product & Technology. As a Data Engineer Intern, you’ll gain exposure to modern software development practices, collaborate with experienced engineers, and learn how high-quality, scalable software is built. You’ll contribute to our all-in-one platform while building a strong foundation for a career in technology.

Many companies offer payroll and human capital management (HCM) solutions, but Paylocity takes technology to the next level. We’ve evolved beyond HCM to a next generation employee experience platform. With uniquely designed solutions that help companies engage employees, we’ve changed how and where work gets done and created a more personalized work environment.

At Paylocity, people matter most and have always been at the heart of our business. As an intern, you’ll be supported through mentorship, hands-on learning, and meaningful work that helps you grow your technical and professional skills while contributing to real products used by thousands of customers. Join Paylocity as we continue to transform the future of technology.

Position Overview

We are looking for a motivated Data Engineering Intern to help bridge the gap between Data Engineering and Data Science by enhancing our semantic metadata systems and improving the trust, quality, and AI-readiness of data across our platform.

This internship is designed for students who are eager to apply academic knowledge to real-world data systems. You will work in a collaborative environment alongside Data Engineers, with exposure to Reporting, Analytics, and Data Science teams.

With guidance and mentorship, you’ll participate in Paylocity’s data development lifecycle, contributing to well-scoped data engineering tasks that enhance our semantic metadata layer, improve data correctness and completeness, and enable effective use of AI and LLMs on top of trusted, well-described data models. Examples of problems you may work on include extending data pipelines, adding data quality tests, managing schema evolution, and curating AI-consumable semantic metadata that supports analytics, reporting, and AI-assisted experiences.

Responsibilities

• Contribute positively to team culture and shared goals
• Participate in team ceremonies such as stand-ups, sprint planning, and retrospectives
• Work on clearly defined data engineering tasks with guidance from mentors and teammates
• Write and maintain SQL transformations to extend and enhance curated, consumable data models
• Add and maintain data quality checks to ensure accuracy and completeness of data
• Contribute to the semantic metadata layer, helping manage schemas, definitions, relationships, and metadata that improve discoverability and AI usability of data
• Support AI readiness by ensuring data models are well-defined, consistently structured, and accompanied by clear semantic context
• Support schema evolution and metadata management for star-schema–based datasets derived from evented and relational transactional data
• Debug and investigate data discrepancies, working with teammates to identify root causes and resolve issues
• Collaborate closely with Data Engineers to improve existing pipelines and data systems
• Learn to read, understand, and modify existing data pipelines and transformations
• Contribute documentation related to data models, transformations, and metadata
• Help validate that data and metadata used for AI or AI-assisted features are accurate, complete, and trustworthy
• Ask questions, seek feedback, and apply learnings to improve your skills
• Demonstrate curiosity and a strong interest in how data is structured, validated, and consumed
• Contribute positively to team culture and shared goals

Required Qualifications

• Currently pursuing (or recently completed) a Bachelor’s degree in Computer Science, Data Engineering, Data Science, or a related technical field
• Coursework, academic projects, or hands-on experience involving SQL and data modeling
• Strong SQL skills and understanding of working with structured data in relational databases
• Experience with at least one programming language (e.g., Python, Java, C#, or similar)
• Familiarity with structured data (tables, schemas, star-schema models) and how it is consumed by analytics or AI systems
• Basic understanding of how AI or LLM-based systems consume data, such as the importance of clean inputs, clear definitions, and consistent schemas
• Strong willingness to learn, ask questions, and take feedback
• Ability to work effectively in a collaborative, team-oriented environment
• Comfortable working on Windows or macOS

Nice to Have (Not Required)

• Exposure to AI, machine learning, or LLM concepts through coursework, projects, or self-study
• Familiarity with semantic layers, metadata systems, or data catalogs
• Experience with dbt, Airflow, or similar data transformation and orchestration tools
• Prior internship, co-op, or personal project experience involving data pipelines or analytics
• Exposure to version control systems such as Git
• Curiosity about how data quality, metadata, and structure impact AI-generated outputs

Paylocity is an equal-opportunity employer. Paylocity is committed to the full inclusion of all individuals. We recruit, train, compensate, and promote regardless of race, religion, color, national origin, sex, disability, age, veteran status, and other protected status as required by applicable law. At Paylocity, we believe diversity makes us better.

We embrace and encourage our employees’ differences in age, culture, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion or spiritual belief, sexual orientation, socio-economic status, veteran status, and other characteristics that make our employees unique. We actively cultivate these differences through our employee resource groups (ERGs), employee experiences, perspectives, talents, and approaches to drive innovation in the software and services we provide our customers.

We comply with federal and state disability laws and make reasonable accommodations for applicants and employees with disabilities. To request reasonable accommodation in the job application or interview process, please contact accessibility@paylocity.com. This email address is exclusively designated for such requests, aligning with federal and state disability laws. Please do not send resumes to this email address, as they will be removed.

Your personal data will be processed for recruitment purposes in accordance with our Notice of Privacy Practices for Job Applicants and applicable data protection laws.

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