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.
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