Data Engineer: ETL Pipelines & AI Data Solutions

LightBox; United States; On-site; USD 95,000 - 135,000; Full time

Job summary

LightBox is seeking a Data Engineer to join the Data Integration team. You will design, build, and maintain reliable data pipelines and data-intensive applications that power LightBox products, working with large, diverse datasets and a range of stakeholders.

This is a hands-on mid-career role focused on practical data problems, ownership of well-defined work, and collaboration with engineering, product, and data teams to deliver trusted, scalable data solutions.

Qualifications

• Bachelor's degree or equivalent practical experience.
• 2+ years building and maintaining production ETLs.
• Proficiency in SQL, Python, and scalable data frameworks.
• Experience with cloud data services (AWS/GCP) and Parquet/Delta Lake.
• Familiarity with workflow orchestration tools and GitHub Actions.

Responsibilities

• Build, test, and maintain batch and streaming data pipelines.
• Transform and organize data for product features and downstream consumers.
• Investigate data issues, troubleshoot root causes, and implement fixes.
• Improve workflows for reliability, efficiency, and maintainability.
• Collaborate with engineers, product, and data stakeholders to deliver solutions.
• Follow team practices for version control, testing, monitoring, and documentation.

Skills

SQL

Python

Data pipelines

Communication

Collaboration

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Spark

DuckDB

Polars

Prefect

Airflow

Dagster

AWS

GCP

Parquet

Delta Lake

GitHub Actions

Job description

LightBox is seeking a Data Engineer to join the Data Integration team. You will design, build, and maintain reliable data pipelines and data-intensive applications that power LightBox products, working with large, diverse datasets and a range of stakeholders.

This is a hands-on mid-career role focused on practical data problems, ownership of well-defined work, and collaboration with engineering, product, and data teams to deliver trusted, scalable data solutions.