Data & ML Engineer

11 days ago

Mason, OH, USASenior

Responsibilities

Design, develop, and operate large-scale data ingestion, transformation, and storage pipelines.
Manage ML infrastructure, CI/CD, DevOps, and MLOps pipelines supporting model training and deployment.
Build ETL/ELT workflows using Azure Data Factory and other orchestration tools.
Structure lakehouse, Azure Data Lake, and Synapse environments for scalable analytics.
Create reusable data pipelines and ML components, including data formats, schemas, and versioning.
Implement monitoring, logging, alerting, security, governance, regulatory compliance, and platform reliability practices.
Partner with Applied Data Scientists to productionize models and translate analytical requirements into scalable engineering solutions.
Lead automation, infrastructure-as-code, solution design, troubleshooting, and root-cause analysis.
Mentor engineers on cloud-native, big data, and MLOps practices.

Bachelor’s degree in Computer Science, Engineering, or a related field.
Proven experience as a Data Engineer, ML Engineer, or Platform Engineer.
Strong hands-on experience with Azure cloud services and big data platforms.
Proficiency in Python, SQL, Scala, and scripting languages.
Strong experience building production-grade data pipelines.
Ability to independently own and deliver complex data and ML engineering solutions end to end.
Preferred qualifications include a master’s degree and experience with Azure Databricks, Spark, Synapse, MLflow, Docker, AKS, APIs, Azure Data Factory, Airflow, SAP CDC, and enterprise data integration.
Strong ownership, collaboration, problem-solving, troubleshooting, reliability, scalability, and operational-excellence skills.

Benefits may include health care, retirement savings, paid time off or vacation, and employee discounts.
The role is full-time and may include a competitive bonus and/or commission plan in addition to the total rewards package.

10,000+ employees