Data Engineer Internship

About the role

The Data Engineering Intern will work directly with the data engineering owner on real production work that AI agents and paying brands depend on. This includes building and hardening ingestion for new structured sources, deduplication and entity-quality tooling, data quality monitoring, and LLM-assisted data cleanup.

Responsibilities

• Build and harden ingestion for new structured sources — commercial enrichment APIs, government datasets, channel-partner catalog feeds.
• Write the connector, handle the noisy edge cases, and document the source's quirks.
• Build the tooling around the entity-resolution system for candidate-pair review interfaces, dedup QA checks, and test fixtures that catch regressions as we scale past 100K entities.
• Help build the observability layer — freshness checks, confidence-distribution dashboards, and alerting that flags when something upstream breaks.
• Prototype and evaluate LLM prompts for disambiguation and structured extraction inside the pipeline, measuring accuracy against a ground-truth set.

Requirements

• Solid SQL and PostgreSQL fundamentals. You can write joins, aggregations, and queries by hand and are comfortable digging into a schema. Bonus for JSONB or query optimization.
• Python or TypeScript. Comfortable writing scripts and small services in at least one; willing to ramp into the other.
• Some data ingestion or scripting experience. A class project, internship, or personal project where you pulled data from a messy API or file and cleaned it into a usable shape.
• Curiosity about LLMs in pipelines — using a model for extraction or disambiguation, not just as a chat feature.
• High agency. You ask good questions, flag when something looks off, and can make progress on a scoped task without constant direction.

Qualifications

• Currently pursuing a BS/MS in CS, data science, or a related field.

Skills

• Coursework or a project involving record linkage, entity matching, or knowledge graphs (nice to have).
• Exposure to data observability or testing tools (nice to have).

Benefits

• Compensation: $45–$55/hour, depending on experience.
• Strong performers will be considered for a full-time return offer.

Pay

• $45–$55/hour, depending on experience.

Schedule

• Full-time (40 hrs/week); 12 weeks, with flexible start/end dates.
• Part-time during term considered for the right local candidate.