Machine Learning Data Engineer (AWS Sagemaker, Python)

JOB TITLE : Machine Learning Data Engineer (AWS Sagemaker, Python) JOB LOCATION : St. Petersburgh, FL or Denver, CO Preferred (Hybrid) (other possible locations Southfield, MI / Memphis, TN or NYC WAGE RANGE

• : $90-105 / hr. JOB NUMBER : 36594249 Required Skills Strong proficiency with SQL and hands-on experience working with Oracle databases. Experience designing and implementing ETL / ELT pipelines and data workflows. Hands-on experience with AWS data services, such as S3, Glue, Redshift, Lambda, and IAM. Proficiency in Python for data engineering (pandas, boto3, pyodbc, etc.). Solid understanding of data modeling, relational databases, and schema design. Familiarity with version control, CI / CD, and automation practices. Ability to collaborate with data scientists to align data structures with model and analytics requirements JOB DESCRIPTION : Duties This role is building and maintaining data pipelines that connect Oracle-based source systems to AWS cloud environments, to provide well-structured data for analysis and machine learning in AWS SageMaker. It includes working closely with data scientists to deliver scalable data workflows as a foundation for predictive modeling and analytics.Develop and maintain data pipelines to extract, transform, and load data from Oracle databases and other systems into AWS environments (S3, Redshift, Glue, etc.). Collaborate with data scientists to ensure data is prepared, cleaned, and optimized for SageMaker-based machine learning workloads. Implement and manage data ingestion frameworks, including batch and streaming pipelines. Automate and schedule data workflows using AWS Glue, Step Functions, or Airflow. Develop and maintain data models, schemas, and cataloging processes for discoverability and consistency. Optimize data processes for performance and cost efficiency. Implement data quality checks, validation, and governance standards. Work with DevOps and security teams to comply with client standards. PreferredExperience integrating data for use in AWS SageMaker or other ML platforms. Exposure to MLOps or ML pipeline orchestration. Familiarity with data cataloging and governance tools (AWS Glue Catalog, Lake Formation). Knowledge of data warehouse design patterns and best practices. Experience with data orchestration tools (e.g., Apache Airflow, Step Functions). Working knowledge of Java is a plus. Education B.S. in Computer Science, MIS or related degree and a minimum of five (5) years of related experience or combination of education, training and experience. Equal opportunity employer as to all protected groups, including protected veterans and individuals with disabilities
• While an hourly range is posted for this position, an eventual hourly rate is determined by a comprehensive salary analysis which considers multiple factors including but not limited to : job-related knowledge, skills and qualifications, education and experience as compared to others in the organization doing substantially similar work, if applicable, and market and business considerations. Benefits offered include medical, dental and vision benefits; dependent care flexible spending account; 401(k) plan; voluntary life / short term disability / whole life / term life / accident and critical illness coverage; employee assistance program; sick leave in accordance with regulation. Benefits may be subject to generally applicable eligibility, waiting period, contribution, and other requirements and conditions. Benefits offered are in accordance with applicable federal, state, and local laws and subject to change at TCM's discretion.