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.

About Your Role:

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.

Your Responsibilities:

• 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.

Your Qualifications:

• 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.

Preferred Qualifications

• 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