Who we are:

Farm Credit Bank of Texas is a $38.9 billion wholesale bank that has been financing agriculture and rural America for over 100 years. Headquartered in Austin, Texas, we provide funding and services to rural lending associations in five states, and we are active in the nation’s capital markets. 

While you may not be familiar with our name, Farm Credit Bank of Texas plays a critical role in supporting the businesses that make it possible for America to maintain access to an affordable and safe food supply, an industry which is one of the most innovative and evolving of our time. And while you help us deliver on our mission, we deliver on our commitment to you as a valued employee by providing competitive compensation, generous health and wellness benefits packages and an attractive hybrid workplace located along the bluffs of the Colorado River just minutes west of downtown Austin. 

We seek out top talent in their fields, whether it be technology, finance, accounting, credit, human resources, or other administrative functions, and welcome you to join us in our mission to feed the world. 

Position Description: 

The Data Engineer Intern supports the enterprise Cloud Data Platform team, working under the guidance of the Director, Data Architecture & AI Toolkit. This role is designed for a Master’s‑level Computer Science student seeking hands‑on experience building, enhancing, and innovating small tools, utilities, and platform components across data engineering, analytics enablement, and ML/AI workflows.

The intern will contribute to production‑adjacent engineering work, focusing on automation, platform utilities, data pipelines, quality checks, and AI‑assisted tooling that improve developer productivity, data reliability, and platform efficiency.

Day-to Day-Duties and 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

Learning & Development Objectives:

• Develop hands‑on experience with modern cloud data platforms
• Learn enterprise‑grade data engineering, operational, and governance practices
• Gain exposure to real‑world ML/AI enablement within a regulated, production environment
• Build a strong foundation for a future full‑time data engineer or platform engineer role

What You Bring to the Team:

Our ideal candidate lives within a commutable distance from our office in Austin, Texas and willing to work onsite. 

It is an important role that covers many skills. This position requires: 

• 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

Education:

• 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)

Important note: We care about your hiring process and take it seriously. A real person will review your applications, meaning response timelines may vary. The interviewing process at Farm Credit Bank of Texas may include phone calls and emails, on-site interviews, and requests for portfolios or demonstrations of work. We cannot personally follow-up with each applicant, and we will do our best to create a professional, respectful, and thorough process for candidates with whom we identify as a potential fit. 

 
A/EOE/M/F/D/V

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