Data Intern

We're looking for a Geospatial Data Engineering Intern to help build and scale our geospatial data infrastructure over the summer. This role is designed for a junior or senior undergraduate with at least one prior internship under their belt, strong data engineering instincts, and the team awareness to ship work in a shared production codebase. You'll get hands-on experience building pipelines that ingest, transform, and serve geospatial data with exposure to AI agent tooling along the way. This role begins as a full-time, 3-month summer internship and then continues part-time through September.You'll work directly with our data team, contributing to operational infrastructure that powers geospatial analysis and decision-making across the organization. Your primary focus will be building reliable, well-documented data pipelines with a geospatial backbone, while getting meaningful exposure to applied AI systems and helping us complete an in-flight migration from Airflow 2 to Airflow 3.About Your Role At Ready ⚡️You’ll spend the majority of your time on geospatial data engineering, with supporting work in geospatial analysis and applied AI.Geospatial Data Engineering (Primary Focus)Build and improve Airflow ELT pipelines that ingest, transform, and serve geospatial datasets at scale, working across both our Airflow 2 and Airflow 3 repositories and actively assisting with the Airflow 2 to 3 migration, including porting DAGs, validating parity, and helping retire legacy pipelinesWrite clean, type-hinted Python and well-structured SQL, including geospatial operations (PostGIS, spatial joins, CRS management) against Athena (Trino), PostgreSQL, Redshift and duckdbDevelop modular dbt models with semantic layer definitions and documented business logic for geospatial tablesContribute to data quality systems, including schema validation, freshness monitoring, and spatial integrity checksSupport DataHub adoption through schema documentation, lineage tracking, and metadata management for geospatial assetsTriage failing DAG runs, read Airflow task logs, and own fixes end-to-endCommunicate progress through documentation, code reviews, and regular updatesGeoData Science (Supporting Research)Contribute to research-oriented analyses such as tree canopy classification, network resiliency analysis, and spatial feature extractionDesign and document reproducible analytical workflows that feed into production pipelinesTranslate complex geospatial methods into clear, accessible outputs for non-technical stakeholdersShare learnings on emerging GeoAI methods and geospatial tooling with the teamAI Engineering (Applied Exposure)Assist with building data agents using tools like LangGraph, LangChain, or Bedrock Agent CoreSupport development and iteration on pipelines and text-to-SQL approaches for natural-language data accessContribute to MCP server development and agent evaluation as neededDocument agent failure modes and help refine prompts based on feedbackA Bit About You 🥇Currently a junior or senior undergraduate (or higher) in Computer Science, Data Science, GIS, Geospatial Engineering, Software Engineering, or a related fieldAt least one prior internship (or equivalent team-based engineering experience); you've shipped code in a shared repo, taken a code review, and worked a ticket end-to-endAvailable to work full-time for 3 months during the summer, then part-time through the fall semesterStrong fundamentals in Python, including classes, inheritance, decorators, type hints, and explicit importsStrong fundamentals in SQL: joins, CTEs, window functions, and aggregationsComfortable working in Git/GitHub with a dev → main PR-to-deploy workflowComfortable on the Unix command line or eager to learn (bash, navigating a filesystem, running scripts)Familiarity with geospatial concepts (CRS, spatial joins, indexing) and tooling such as PostGIS, GeoPandas, or QGIS is a plusExposure to AWS or similar cloud providers; ideally S3, IAM, Athena, Glue, ECS, or RedshiftExperience with Airflow or similar orchestration tools is a plus (or strong eagerness to learn quickly. You'll be ramping on two versions in parallel and contributing directly to our migration effort)Familiarity with dbt, Pandas, or Parquet/columnar data is a plusExposure to AI agent architectures (e.g., ReAct) and protocols (A2A, MCP, AG-UI) is a plusAbout Ready 🚀Creative problem solvers approaching a legacy industry with a new point of viewHumble but ambitious, knowledgeable but curious, persistent but not obnoxiousConcise and effective in written and spoken communicationComfortable working remotelyOne team, one dreamAbout What You Get…Competitive hourly wage - $35-$40 per hour100% remote work from homeOpportunities to learn and grow – all things startupsA chance to play a role in defining the roadmap as we pursue a bold vision and and a big goalWork from (almost) anywhere. Ready is a remote-first company, but for security and compliance reasons, employees are not permitted to work from China (excluding Hong Kong, Macau, and Taiwan), Russia, Iran, or North Korea. These restrictions are in place to protect our systems, data, and intellectual property. To get away - we all convene 1-2x a year for [optional, encouraged] retreatsThe charter to realize a market that is set to receive $65 billion in grant funding across the United States