Data Solutions Engineer

Paychex is reimagining how businesses manage their workforce by bringing payroll, HR, benefits, and advisory services together into a single connected HCM platform. As Paychex and Paycor come together, we're combining innovative technology, data-driven insights, AI, and human expertise to help organizations work smarter, support their people, and achieve better business outcomes. This is an exciting time to join our team as we continue to invest in innovation, simplify client experiences, and shape the future of work. At Paychex, you'll have the opportunity to grow your career, make a meaningful impact, and be part of something bigger as One Paychex. Overview The Data Solutions Engineer will play a key role in integrating, architecting, and optimizing data systems to support data monetization, analytics, machine learning, artificial intelligence, and large-scale data operations. The role will involve collaborating with cross-functional teams to develop and deploy end-to-end solutions that improve data availability, scalability, security, and overall performance, ensuring alignment with both business goals and technical best practices. Responsibilities Work with architects, operations teams, and data scientists to define data requirements and translate them into actionable data strategies. Design, build and optimize data systems for performance, scalability, ease of use and reliability, leveraging tools for observability and troubleshooting; includes exploration of multiple solution options for any given integration objective and analysis of associated advantages and disadvantages. Enhance system integration for data workflows, ensuring performance metrics are met and all integrations remain stable and secure. Collaborate on the integration of AI/ML platforms, ensuring seamless multi-cloud and hybrid cloud operations Build and optimize data pipelines to support data extraction, transformation, and loading (ETL) processes using technologies such as Databricks, Snowflake, and Azure Data Factory. Develop automation frameworks and CI/CD pipelines using tools like Terraform, GitHub Actions, and Azure Pipelines for efficient and reliable data deployment. Ensure data pipelines comply with security, privacy, and compliance standards. Work closely with internal teams, including data engineers, data scientists, analytics engineers and business stakeholders, to understand platform solution needs. Mentor junior engineers, providing guidance on best practices and technologies. Evangelize integration practices and knowledge within the organization to improve collaboration across teams. Stay abreast of the latest trends in cloud computing, machine learning, AI, and data engineering. Explore new technologies and methodologies to continuously improve systems, tools, and data processes. Qualifications Bachelor's Degree in Computer Science, Data Science, Engineering, or related field - Required 7 years of experience in data engineering, software engineering, systems integration, or a related field, with demonstrated expertise in designing, building, and deploying scalable data solutions. 4 years of experience in cloud technologies (Azure, AWS, Google Cloud) and large-scale data processing. 1 year of experience in machine learning model deployment, AI/ML solutions, and data pipeline architecture. Less than 1 year of experience in Familiarity with AI/ML frameworks, DevOps practices, and MLOps processes for integrating AI solutions. Snowflake SnowPro - Preferred Live the Paychex Values Act with uncompromising integrity. Provide outstanding service and build trusted relationships. Drive innovation in our products and services and continually improve our processes. Work in partnership and support each other. Be personally accountable and deliver on commitments. Treat each other with respect and dignity. What's in it for you? We value your well-being: We provide over 21 comprehensive rewards, including medical coverage, virtual