DATA ENGINEER

W2 CONTRACT - Hybrid

ST. PETERSBURG, FL

No Third Parties - GC/USC 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.).

• 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. 

Required Skills:

• 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 Skills:

•  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.