Data Engineer

W2 contract for local Tampa Bay candidates only!!

Our client located in St.Petersburg, FL is seeking a Data Engineer to build and maintain 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.

Duties

• Develop and maintain data pipelines to extract, transform, and load data from Oracle databases and other systems into AWS environments (S3, Redshift, Glue, etc.).
• Setting up pipelines to feed the needs of the data scientists
• SQL connections to load files
• All new pipelines need to be created as there are no existing pipelines/Mostly batch pipelines
• 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.

Skills

Required

• Strong proficiency with SQL and hands-on experience working with Oracle databases.
• Strong experience in batch processing.
• 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.