Data Solutions Engineer: AI/ML Pipelines & Cloud DataOps

Paychex Deutschland GmbH; City of Rochester, Northern (NY, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health coverage

401(k) match

Paid time off

Tuition reimbursement

Adoption assistance

Job summary

Paychex is seeking a Data Solutions Engineer to design, build, and optimize data systems for analytics, AI, and data monetization. You will partner with data scientists and engineers to deliver scalable, secure pipelines and multi-cloud integrations.

Responsibilities include ETL design with Databricks and Snowflake, using Azure Data Factory, and implementing CI/CD with Terraform and GitHub Actions, while upholding data governance and performance.

Qualifications

• Bachelor's degree in a related field and strong foundations in data engineering.
• 7+ years of experience designing and deploying scalable data solutions.
• 4+ years in cloud technologies and large-scale data processing.
• 1 year in ML/AI deployment and data pipeline architecture.

Responsibilities

• Define data requirements with architects, translate into data strategies, and design scalable data systems.
• Build and optimize ETL pipelines using Databricks, Snowflake, and Azure Data Factory; ensure security and compliance.
• Collaborate with data engineers, data scientists, analytics engineers and business stakeholders; mentor junior engineers and promote best practices.
• Stay current with cloud, ML, and data engineering trends to continuously improve systems.

Skills

Data engineering

Cloud technologies

ETL pipelines

CI/CD

AI/ML integration

Stakeholder collaboration

Education

Bachelor's Degree in CS/DS/Engineering

Tools

Databricks

Snowflake

Azure Data Factory

Terraform

GitHub Actions

Azure Pipelines

Job description

Paychex is seeking a Data Solutions Engineer to design, build, and optimize data systems for analytics, AI, and data monetization. You will partner with data scientists and engineers to deliver scalable, secure pipelines and multi-cloud integrations.

Responsibilities include ETL design with Databricks and Snowflake, using Azure Data Factory, and implementing CI/CD with Terraform and GitHub Actions, while upholding data governance and performance.