> Markdown version of [/jobs/ext/1169229-data-solutions-engineer](https://www.wearedevelopers.com/jobs/ext/1169229-data-solutions-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Solutions Engineer - **Company:** Paychex Inc. - **Location:** Cincinnati, OH, United States - **Experience:** Starter - **Salary:** $91,526.0 - $156,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Cloud Computing, Information Engineering, Extract Transform Load (ETL), Data Mining, Data Systems, DevOps, Github, Machine Learning, Tensorflow, Azure Machine Learning, Software Engineering, Systems Integration, Google Cloud, Informatica Powercenter, System Availability, Snowflake, Multi-Cloud, HybridCloud, Information Technology, Machine Learning Operations, Terraform, Data Pipelines, Atlassian Bamboo, Databricks - **Published:** July 3, 2026 - **Apply:** https://www.juju.com/job/00000000gcxwjo ## About the Role + 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 ## Description 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 Informatica IDMC. 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. Provide occasional operational support and troubleshooting for existing processes and systems. + 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. Note: Candidates must be legally authorized to work in the United States on a permanent basis. 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