Role: Senior Data Engineer

Function: Data Engineering

Location: Not specified

Type: Full-time

Compensation: Not specified

Industry: Information Technology & Services / AI / Computer Vision

About Company

The company is an AI-powered technology firm based in Santa Monica, California, founded in 2017. It uses computer vision and deep learning to enable checkout-free, frictionless experiences at physical locations.

Today, it is the largest parking operator in North America, operating across 4,500+ locations. The technology is expanding into retail, fueling, airports, and beyond.

Backed by $4.1B in Series D funding, the company has a team of 20,000 and is scaling fast.

Position Overview

As a Senior Data Engineer, you will play a key role in shaping both customer-facing and business-facing data products that align with the company's mission. Your technical expertise will contribute to designing and building extensive data sets that impact thousands of internal users and millions of members. You will join a world-class data engineering team dedicated to advancing your skills and career in data engineering and beyond.

Role & Responsibilities

• Collaborate with engineers, product managers, and data scientists to develop end-to-end data pipelines, solutions, and foundational data sets
• Design and own the data architecture for large-scale projects, making informed decisions about design and operational trade-offs
• Build, launch, and optimize sophisticated data pipelines, data models, and visualizations that support diverse use cases across multiple products or domains
• Define and manage Service Level Agreements (SLAs) for all data sets within areas of ownership
• Implement data security models based on privacy requirements, ensure compliance with safeguards, and evolve data governance processes
• Solve complex data integration challenges using optimal ETL/ELT patterns, frameworks, and query techniques for both structured and unstructured data sources
• Optimize pipelines, dashboards, frameworks, and systems to streamline data artifact development
• Mentor team members, providing and receiving actionable feedback to foster skill growth and collaboration

Must Have Criteria

• 5+ years of experience in data engineering, data warehousing, and ETL/ELT, working with large data sets in the cloud
• Strong proficiency in SQL and data modeling, with hands-on experience in Snowflake and dbt
• 5+ years of Python development experience, including building scalable Big Data solutions and ETL ecosystems
• Hands-on experience with RDBMS — MySQL, PostgreSQL, and MS SQL Server
• Experience with Apache Airflow for pipeline orchestration and working knowledge of CI/CD pipelines
• Experience with Spark and PySpark for large-scale data processing
• Strong proficiency in Terraform for infrastructure-as-code

Nice to Have

• Master's degree in Computer Science, Computer Engineering, or a related technical field
• Experience with Automic or similar enterprise job scheduling/integration tools
• Prior experience in a high-growth startup or scaleup environment handling petabyte-scale data
• Familiarity with AWS data services (S3, Glue, Redshift, Lambda) in production environments
• Experience with Datadog for pipeline observability and monitoring

What We Offer

• Opportunity to build data infrastructure that impacts millions of real-world transactions daily
• Work with a world-class data engineering team at a Series D company with $4.1B in funding
• Fast-paced, ownership-driven culture that encourages innovation and challenges the status quo
• Career growth opportunities in data engineering and adjacent technical domains
• Exposure to cutting-edge AI and computer vision technology at massive scale