Data Quality AI Intern (61_2026.3)

Affinity Solutions (Affinity) is the leading consumer purchase insights company. We provide a complete view of U.S. and U.K. consumer spending, across and between brands, via exclusive access to fully permissioned data from over 100 million consumers. Our proprietary AI technology, Comet™, transforms these purchase signals into actionable insights for business and marketing leaders to drive optimal outcomes and build lasting customer relationships. Visit https://www.affinitysolutions.com to discover how we’re shaping the future of consumer purchase insights.

We are looking for a motivated Data Quality AI Engineer Intern to join our Data Engineering team. You will work on production-scale data platforms to build automated data quality solutions, AI-powered tools, and scalable data pipelines. This role combines data quality engineering, software development, cloud technologies, and AI to improve data reliability, automate validation processes, and deliver actionable insights.

• →Develop and automate AI/ML data quality frameworks to validate datasets, features, embeddings, and AI-generated outputs for accuracy and reliability.
• →Build data profiling, validation, reconciliation, and anomaly detection workflows using Python, SQL, Spark, and cloud technologies.
• →Implement quality checks for LLM and Generative AI applications, including prompt validation, response evaluation, and model output monitoring.
• →Monitor AI data pipelines for data drift, schema changes, completeness, and consistency to ensure reliable model performance.
• →Collaborate with Data Engineering and ML teams to design scalable QA frameworks, dashboards, alerts, and automated testing solutions.

• Pursuing a BS/MS in Computer Science, Data Science, Engineering, Information Systems, or a related field.
• Strong SQL skills (joins, CTEs, window functions, aggregations).
• Proficiency in Python for automation, APIs, and data processing.
• Familiarity with data warehouses such as Snowflake, Redshift, BigQuery, or Databricks.
• Exposure to cloud platforms (AWS, Azure, or GCP) and data pipeline concepts.
• Understanding of REST APIs, software engineering fundamentals, and version control (Git).
• Strong analytical, problem-solving, and communication skills.

• Experience with Spark/PySpark, Airflow, dbt, or similar data engineering tools.
• Exposure to AI/LLMs, prompt engineering, MCP frameworks, or chatbot development.
• Familiarity with data quality, ETL/ELT, data governance, and monitoring frameworks.
• Experience working with large-scale datasets and building dashboards or reporting solutions.
• Knowledge of machine learning, feature engineering, or data privacy concepts is a plus.

Salary Range: $25/hr. for undergraduate students, $30/hr. for current graduate students

Office Hours: 9am – 5:30pm