Data Engineer - Developer Platform

We’re looking for a Data Engineer to join the team that makes Wix a data-driven company.

Our team builds the data infrastructure and products that support Wix’s key developer experiences.

You’ll own the pipelines, models, and tools that power decisions across the company.

This is a role for someone who combines business thinking with strong engineering skills and works with AI as part of their daily workflow. We expect you to be comfortable with AI coding agents and use them to improve development, testing, documentation, and debugging.

You’ll work closely with the business analysts, product managers, and stakeholders to understand the business needs behind the data, and turn them into reliable, production-grade data solutions.

Job Description

• Design, build, and maintain robust pipelines feeding both DWH and production processes
• Own pipeline orchestration in Apache Airflow end to end, including DAG design, monitoring, alerting, and production reliability
• Design the data models behind our core domains and the contracts that downstream consumers depend on
• Partner with business analysts, PMs, and business stakeholders to translate product and business questions into stable, qualified, and well-modeled data
• Work with a variety of data sources including product events, application data, APIs, operational databases, logs, and third-party systems
• Debug and solve data quality, pipeline, performance, and reliability issues
• Use and create AI agents and LLM-based tooling to improve development, testing, documentation, and root cause analysis
• Be part of the team and adopt effective ways of using AI tools in the engineering workflow
  
  

• 3+ years in data engineering or a similar data-focused engineering role
• Strong hands-on Python and SQL skills, with the ability to write clean, performant, and maintainable code
• Proven track record of building and running code in large scale production environments
• Deep, hands-on Apache Airflow experience, including ownership of production DAGs at scale
• Deep data modeling expertise and the ability to design clean, scalable data assets that hold up as the business changes
• Strong business and product orientation. You care about what the metric means, not just whether the job succeeded
• Experience working with PMs, analysts, and business stakeholders to understand requirements and build the right data solutions
• Practical experience using AI coding agents and LLM-based tools as part of your daily engineering workflow
• Experience working with large and varied data sources including product events, application data, APIs, operational databases, logs, and third-party systems
• Strong debugging and problem-solving skills around data quality, pipeline failures, performance, and reliability
  
  

• Experience running data workloads in containerized or Kubernetes-based environments
• Experience with large-scale or distributed processing using Spark / PySpark
• Experience with query engines such as Trino
• Experience with CI/CD and software engineering best practices
• Experience building internal tooling or agents on top of LLMs