Data Engineer Intern - Cloud Data Platform, ML… at American… · Austin

Summary: American AgCredit is a $38.9 billion wholesale bank that has been financing agriculture and rural America for over 100 years. The Data Engineer Intern will support the enterprise Cloud Data Platform team by assisting in the design and development of data pipelines and automation tools, while gaining hands-on experience in data engineering and ML/AI workflows. Responsibilities: - Assist in the design and development of data pipelines, ingestion utilities, and transformation logic on cloud data platforms (Databricks, Azure, etc) - Build small internal tools and utilities to support platform operations, developer experience, and governance automation - Assist in implementing data quality scorecard framework covering data validation, reconciliation, and quality checks - Experiment with AI‑assisted tooling, such as metadata enrichment, data quality recommendations, or intelligent monitoring prototypes - Collaborate with platform and analytics teams on proof‑of‑concepts involving ML or GenAI capabilities - Support implementation of bronze / silver / gold style data processing patterns under senior engineer guidance - Develop reusable scripts, libraries, and utilities to simplify common platform tasks - Assist with automation for monitoring, validation, data quality checks, and operational reporting - Contribute to CI/CD pipelines, configuration scripts, and deployment automation where applicable - Support development of data preparation and feature engineering utilities for ML and AI use cases - Gain exposure to data platform operations, including incident analysis, performance tuning, and cost optimization activities - Help document testing approaches and quality metrics - Create and maintain technical documentation, diagrams, and runbooks for tools and utilities developed - Present work outcomes and learnings to the platform engineering team Required Qualifications: - Strong foundation in Python and SQL - Familiarity with data engineering concepts such as ETL/ELT, data modeling, and batch & stream processing - Exposure to cloud platforms (Databricks, Azure, AWS, or GCP) and modern data tools - Detailed understanding of ML concepts such as feature engineering, training pipelines, or model inputs is a plus - Experience using Git and collaborative development workflows - Strong analytical and problem-solving skills - Curiosity and willingness to learn complex data and platform concepts - Ability to work independently on well-defined tasks while collaborating with senior engineers - Ability to collaborate and excel in complex, cross-functional teams involving data engineers, business analysts, and stakeholders - Clear written and verbal communication skills - Attention to detail and quality-focused mindset - Currently pursuing a Master's degree in Computer Science, Data Science, Software Engineering, or related field - OR recently completed a Master's degree in Computer Science or a related field and eligible to work in the U.S. under Optional Practical Training (OPT) Required Skills: Python, SQL, Data engineering, ETL, ELT, Data modeling, Batch processing, Stream processing, Cloud platforms, Databricks, Azure, AWS, GCP, Git, Machine learning, Feature engineering, Training pipelines, Analytical skills Benefits: Competitive compensation, Generous health and wellness benefits packages