Data & ML Engineer

2 hours ago

Dallas, TX, 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.
Design ETL/ELT workflows using Azure Data Factory and orchestration tools.
Structure Lakehouse, Azure Data Lake, and Synapse environments for scalable analytics.
Build reusable data pipelines and ML components and organize data formats, schemas, and versioning.
Monitor platform performance, cost, reliability, availability, security, governance, and regulatory compliance.
Collaborate with Applied Data Scientists to productionize models.
Lead automation-first, infrastructure-as-code, scalable platform, troubleshooting, and root-cause-analysis practices.
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.
Master’s degree in Computer Science, Engineering, or a related discipline is preferred.
Preferred experience includes Azure Databricks, Spark, Synapse, MLFlow, Docker, AKS, APIs, containerized ML workloads, Azure Data Factory, Airflow, SAP CDC, and enterprise data integration.

Full-time position with health care, retirement savings, paid time off/vacation, and employee discounts potentially included in the total rewards package.
Competitive bonus and/or commission plan may complement the total rewards package.
The position is not available for visa sponsorship or transfer; candidates must be authorized to work in the United States.

10,000+ employees