Role : Data Engineer – ML Infrastructure Location : Cincinnati, OH 45202 (Onsite) Duration: : 12+ Months Key Responsibilities: • Build and maintain scalable, high-quality data pipelines to support ML model training and deployment. • Collaborate with data scientists and ML engineers to deliver curated, production-ready datasets. • Contribute to the foundation and best practices for machine learning data infrastructure across the bank. • Assist in designing and implementing robust data workflows using modern tools and platforms. Required Qualifications: • 1–5 years of professional experience in data engineering or a related field. • Strong proficiency in SQL and Python. • Excellent collaboration skills and an eagerness to work closely with cross-functional teams. Preferred Skills: • Experience working on ML-related projects or supporting data science teams. • Familiarity with cloud platforms, especially AWS SageMaker. • Knowledge of Snowflake, dbt, or other modern data transformation tools. • Exposure to ML tools like Databricks is a plus. Additional Information: • This role requires onsite presence at least four days a week at the Cincinnati office. • Hands-on role with high visibility and direct impact on enterprise ML initiatives. • A great opportunity for early-career professionals eager to grow in the machine learning and data engineering space