Sr. Data Engineer (SQL+Python+AWS)

looking for a Sr. Data Engineer (SQL+Python+AWS) to work on a 12+ Months, Contract (potential Extension or may Convert to Full-time) = Hybrid at St. Petersburg, FL 33716 with a Direct Financial Client = only on W2 for US Citizen or Green Card Holders. Notes from the Hiring Manager: • Setting up Python environments and data structures to support the Data Science/ML team. • No prior Data Science or Machine Learning experience required. • Role involves building new data pipelines and managing file-loading connections. • Strong SQL skills are essential. • Contract-to-hire position. • Hybrid role based in St. Pete, FL (33716) only. 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 RJ standards. Skills: Required: • 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 Preferred: • Experience 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.