Data Engineer — AI/ML Data Pipelines

Paychex Deutschland GmbH; City of Rochester (NY); On-site; USD 110,000 - 170,000; Full time

Job summary

Paychex Deutschland GmbH is seeking a data engineering professional to source, extract, and manipulate large datasets for analytics, ML, and AI initiatives. You will collaborate with architects, data owners, and stakeholders to groom the data platform backlog and deliver scalable automation for high-throughput data processing.

The role requires strong SQL, Python, Spark, and big data tooling experience, with a focus on data security and compliance in an agile environment.

Qualifications

• Bachelor's Degree in Computer Science, Data Science, or Engineering required.
• 4+ years with SQL, Snowflake, Databricks, Spark or similar big data tech.
• 2+ years with Azure Data Factory, Data Lake, Databricks, Cosmos DB.
• 4 years building data pipelines and architectures to answer business questions.
• Proficiency in Python, SQL, PySpark, or R.
• Experience with Agile methodologies.

Responsibilities

• Source, extract, and manipulate large data sets for Analytics, ML, and AI needs.
• Coordinate data platform backlog with architects, data owners, and stakeholders.
• Deliver automation to ensure high throughput and performance of the data & analytics platform.
• Ensure data extraction, transformation, and loading meet data security & compliance requirements.
• Engage with data source leads to align with standards.
• Create data tools to assist data scientists in building models for Paychex products.

Skills

Communication

Problem Solving

Data thinking

Education

Bachelor's Degree in Computer Science

Tools

Snowflake

Databricks

Spark

Azure Data Factory

Data Lake

Cosmos DB

Python

SQL

Azure ML

GitHub Actions

Job description

Paychex Deutschland GmbH is seeking a data engineering professional to source, extract, and manipulate large datasets for analytics, ML, and AI initiatives. You will collaborate with architects, data owners, and stakeholders to groom the data platform backlog and deliver scalable automation for high-throughput data processing.

The role requires strong SQL, Python, Spark, and big data tooling experience, with a focus on data security and compliance in an agile environment.