Senior Data Engineer: ML Pipelines for Chemical Data

Eurofins USA Environment Testing; Stafford (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical insurance

401(k) with company match

Paid time off

Job summary

Eurofins USA Environment Testing is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure supporting ML model training, deployment, and analysis. You will work closely with ML engineers and chemists to handle complex chemical data, transform it into reliable datasets, and ensure data quality and governance across pipelines.

The role requires strong Python expertise, cloud data platform experience (Azure preferred), and familiarity with data

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field (or equivalent practical experience).
• Expert-level Python with data engineering libraries (Pandas, NumPy).
• Experience with cloud data platforms (Azure preferred).
• Hands-on experience building ETL/ELT pipelines and data models.
• Familiarity with MLOps concepts and ML tooling.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines for chemical data.
• Develop and manage data models and data lake/warehouse for ML feature engineering.
• Collaborate with ML engineers to deploy and retrain models.
• Implement data quality checks and governance for reproducible data.

Skills

Python proficiency

Data engineering

English proficiency

Problem solving

Communication

Education

Bachelor's or Master’s in CS/Data Eng/related

Tools

Azure Cloud

Azure Data Lake Storage

Azure Compute VMs

Azure ML Studio

Airflow

SQL (PostgreSQL)

Git

MLflow/Kubeflow

Job description

Eurofins USA Environment Testing is seeking a Senior Data Engineer to design, build, and maintain scalable data pipelines and infrastructure supporting ML model training, deployment, and analysis. You will work closely with ML engineers and chemists to handle complex chemical data, transform it into reliable datasets, and ensure data quality and governance across pipelines.

The role requires strong Python expertise, cloud data platform experience (Azure preferred), and familiarity with data