Overview
On Site
Depends on Experience
Contract - W2
Contract - 6 Month(s)
Skills
SQL
Python
Data Engineering
Machine Learning Data Pipelines
AWS
AWS SageMaker
Snowflake
dbt
Cloud Data Platforms
Data Modeling
ETL/ELT
Data Warehousing
Databricks
Collaboration with Data Science Teams
Job Details
Data Engineer Machine Learning Data Enablement Location: Onsite (4 days/week, Monday Thursday) Location not specified
Experience: 10+ yrs.
Skills / Tools: SQL, Python, Data Engineering, Machine Learning Data Pipelines, AWS, AWS SageMaker, Snowflake, dbt, Cloud Data Platforms, Data Modeling, ETL/ELT, Data Warehousing, Databricks, Collaboration with Data Science Teams
Duration: 6+ Months
Job Description
- Fifth Third Bank is hiring a Data Engineer to join its newly launched Machine Learning Data Enablement squad within the Data Insights Tribe. This team focuses on building high-quality, scalable data pipelines that support machine learning models deployed across the enterprise using AWS SageMaker.
- This role is ideal for an early-career professional eager to grow in a hands-on data engineering position. The Data Engineer will work closely with data scientists and ML engineers to deliver curated, production-ready datasets and enable efficient ML workflows through robust data infrastructure.
- The ideal candidate has strong SQL and Python skills, a collaborative mindset, and an interest in modern data tooling. Experience with Snowflake, dbt, cloud data platforms, or exposure to machine learning tools such as SageMaker or Databricks is a plus. Training and learning opportunities will be provided where needed.
- This is a high-impact, high-visibility role, offering the opportunity to help define and scale how data powers machine learning across the bank.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.