Data Solutions Engineer

Paychex • City of Rochester, NY

3d

About The Position

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.

Requirements

• 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.

Nice To Haves

• Snowflake SnowPro - Preferred

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.

Benefits

• medical coverage
• virtual wellness classes
• tuition reimbursement
• 401(k) + employer match
• adoption assistance
• financial assistance
• paid time off
• company holidays
• culture days
• work-life balance programs
• training and development programs
• paid time off for volunteerism

What This Job Offers

• Job Type: Full-time
• Career Level: Senior