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Self Inspection | Remote — Latin America | 5+ years experience

About the Role

Self Inspection is transforming vehicle inspections with AI-powered computer vision — turning a smartphone camera into an inspection tool that processes vehicle photos, videos, damage assessments, and condition reports at scale.

You'll build and own the data infrastructure that powers our analytics, AI systems, customer reporting, and operational insights: scalable pipelines, optimized storage and processing, and reliable access to high-quality data across the organization. You'll work closely with backend engineers, computer vision engineers, product, and leadership — supporting both business analytics and machine learning initiatives.

This is a hands-on engineering role. Great fit if you love building robust data systems end to end and want your pipelines feeding real AI products. Not a fit if you're looking to manage from an architecture diagram.

What You'll Do

- Design, build, and maintain scalable batch and real-time data pipelines
- Build ingestion for inspection data, AI predictions, reports, images, videos, and customer integrations
- Implement ETL/ELT workflows that turn raw data into analytics-ready datasets
- Design data models and manage warehouses, lakes, and relational databases — optimizing query performance and storage
- Build the datasets and pipelines the Computer Vision and AI teams train on, including dataset versioning and reproducibility
- Implement automated data validation, quality checks,



monitoring, and alerting for critical workflows
- Partner with engineering, product, AI, and business teams to define KPIs and document data models and best practices

Success looks like: reliable, well-monitored pipelines supporting product, analytics, and AI; high-quality datasets available for reporting and model training; and fast access to trusted data across the company. Must-Haves
- 5+ years in Data Engineering building and maintaining production-grade pipelines
- Large-scale datasets in cloud environments (AWS preferred)
- Expert-level SQL and strong Python
- Apache Airflow and dbt
- PostgreSQL plus a data warehouse (Snowflake, BigQuery, or Redshift)
- Experience supporting analytics and machine learning workloads
- Data quality and validation frameworks
- Located in Latin America with 4 hours of daily overlap with PST (7–11 AM)

Nice-to-Have Apache Spark · Kafka or other event streaming · MLflow, Weights & Biases · Delta Lake, Apache Iceberg · experience supporting Computer Vision/ML teams · pipelines for image, video, or unstructured media · MLOps, feature engineering, data lineage · event-driven architectures and microservices · startup environments

We don't expect all of it. Strong on SQL, Python, Airflow/dbt, and production pipelines at scale — apply.

Terms unlimited PTO · company computer after 3-month probation period

Hiring Process

1. Apply — you'll be invited to a 20-minute AI interview
2. Latin Remote Workers interview — virtual, with our team
3. Final interviews — with the Self Inspection team

📌 Senior Data Engineer (Argentina)
🏢 Latin Remote Workers
📍 Argentina