Job Title: Data Engineer Location: Texas (Remote) Job Type: Contract Travel: 10% to Dallas/ Dallas Airport Must Have • Python Expert (idiomatic python 3.11+) • Heavy data engineering experience. • Experience working alongside Data Scientists, assisting with model training and prediction frameworks. Job Summary We're seeking an experienced Data Engineer with deep expertise in Python 3.11+ who can design and develop high-throughput data pipelines and collaborate closely with Data Scientists on model training and production prediction systems. Familiarity with Azure Machine Learning and Azure Data Factory is a strong advantage. Key Responsibilities • Design, build, and maintain scalable ETL/ELT data pipelines in idiomatic Python 3.11+, handling both batch and streaming workloads • Collaborate with Data Scientists to operationalize ML models: assist in model training, deployment, and end-to-end prediction frameworks . • Optimize data storage solutions (SQL/NoSQL/data warehouses) and implement transformations in Python and SQL for analytical and ML use cases . • Integrate and manage message queues (e.g., Kafka, RabbitMQ) for asynchronous data processing workflows • Monitor, log, troubleshoot, and optimize data pipeline performance and reliability • (Nice to have) Design and maintain ML workflows using Azure Machine Learning, and manage data orchestration with Azure Data Factory Required Qualifications • 4+ years of professional experience in Python (3.11+), including clean, idiomatic code practices • Proven history of building scalable data pipelines, data models, and ETL/ELT workflows • Strong SQL and database expertise (PostgreSQL, DynamoDB, or equivalents) . • Experience integrating REST APIs and message-driven frameworks in data engineering contexts . • Familiarity with version control and CI/CD systems (e.g., GitLab, Azure DevOps) . • Excellent collaboration and communication skills with technical and data science stakeholders Preferred (Nice-to-Have) • Hands-on experience with Azure Machine Learning and Azure Data Factory • Familiarity with Azure Databricks, Spark/PySpark, or similar big data frameworks • Experience with Airflow or similar orchestration tools • Experience containerizing workloads (Docker/Kubernetes) for deployment and scaling • Experience in MLOps or assisting production ML systems with monitoring, retraining, and versioning.