Engineering - Data - Data Engineer

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

Data Engineer

Data Integration Team | LightBox

• Department: Data Integration
• Reports to: Manager, Data Engineering

Position Overview

LightBox is seeking a Data Engineer to join the Data Integration team. This role designs, builds, and maintains reliable data pipelines, data-intensive applications, and AI-enabled automation that support LightBox products. The successful candidate will work with large, diverse datasets and partner with engineering, product, and data stakeholders to deliver trusted, scalable data solutions.

This is a hands-on role for a mid-career engineer who enjoys solving practical data problems and taking ownership of well-defined work with support from the team.

What You Will Do

• Build, test, and maintain batch and event-driven data pipelines and ETL/ELT workflows.
• Transform, validate, and organize data for product features and downstream consumers.
• Investigate pipeline and data-quality issues, troubleshoot root causes, and implement fixes.
• Improve existing workflows for reliability, efficiency, and maintainability; support platform modernization.
• Work with engineering, product, and data stakeholders to understand requirements and deliver solutions.
• Follow team practices for version control, code review, testing, monitoring, and documentation.

What You Bring

Required qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 2+ years of relevant industry experience including building and maintaining production ETLs.
• High proficiency in at least one SQL dialect, Python, and at least one scalable data processing framework (Spark, DuckDB, Polars, etc.)
• Experience designing, building, and operating batch and/or event-driven data pipelines.
• Experience with a workflow orchestration platform (Prefect, Airflow, Dagster, etc.), and familiarity with distributed data processing.
• Experience with cloud data and infrastructure services in AWS and/or GCP.
• Familiarity with modern data storage formats and technologies, including Apache Parquet and Delta Lake.
• Working knowledge of GitHub workflows, including pull requests, code review, branching, and CI/CD automation with GitHub Actions.
• Clear communication, curiosity, and a collaborative approach to problem-solving.

Bonus qualifications:

• Experience using Codex or other LLM-assisted development tools to generate and refine code from specifications, with strong code-review and testing practices.
• Experience processing large scale geospatial or location-based data.
• Experience with data modeling and designing data solutions for multiple product or business use cases.
• Experience supporting production data workflows with monitoring, alerting, and incident-response practices.

Working at LightBox

This job description summarizes the primary responsibilities and qualifications for the role. Responsibilities may change as business needs evolve. The role may occasionally require work outside standard business hours to meet deadlines or support customers and production operations.

LightBox is an equal opportunity employer. We are committed to providing equal employment opportunities to all employees and applicants without regard to protected characteristics under applicable law.