Job Details

Type: Equity-based (Seed stage) | Future paid opportunity

Role Overview

We're seeking a Data Engineer to own the ETL pipelines and feature engineering layer powering CASEY's AI systems. You'll build the data backbone that allows our models to learn, adapt, and scale.

Responsibilities

• Design and maintain ETL pipelines for multi-source data ingestion (structured & unstructured).
• Ensure data quality, validation, versioning, and lineage across all datasets.
• Develop and optimize feature engineering workflows for ML models.
• Work with SQL, PySpark, or Snowflake to manage large-scale analytics data.
• Collaborate with the ML team to deliver clean, ready-to-train datasets.

Requirements

• Expertise in SQL (Advanced) and Python (Intermediate).
• Hands‑on experience with ETL tools (Airflow, Spark, Pandas, etc.).
• Understanding of data modeling, schema design, and pipeline optimization.
• Familiarity with cloud‑based data storage (AWS S3, BigQuery, or Postgres).
• Experience building reproducible and versioned data workflows.
• Proof of Work: A GitHub portfolio is required. Applications without relevant repositories or code samples will not be considered.

Why Us?

Join CASEY as a core team member and gain equity in a mission‑driven AI venture shaping the future of career guidance. You'll have the opportunity to influence product, culture, and technology from day one. This is an opportunity to change Career Development forever.

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