MarTech Data & Integration Developer

The MarTech Data & Integration Developer will help develop and support the data pipelines and integrations that power our marketing technology ecosystem.

As our MarTech capabilities expand across personalization, customer engagement, audience management, experimentation, and measurement, reliable access to customer and behavioral data is increasingly important. This role will work across application development, data engineering, and analytics to help ensure MarTech platforms receive accurate and usable data.

This is a hands-on development role well suited for someone with a foundation in software development, data engineering, analytics, or data science who is interested in growing their skills within a modern MarTech environment.

Key Responsibilities

• Develop, maintain, and support data pipelines used by MarTech platforms and digital customer experiences.
• Work with customer, behavioral, transactional, campaign, and clickstream data across enterprise systems.
• Develop SQL transformations and datasets in Snowflake to support personalization, audience creation, campaign activation, and analysis.
• Use Python and SQL to automate data processing, validate integrations, troubleshoot issues, and perform data analysis.
• Develop and support integrations using APIs, event streams, and batch data processing.
• Build and maintain scheduled data workflows using technologies such as Apache Airflow.
• Work with Product, Marketing, Engineering, Analytics, and Data teams to understand data and integration requirements.
• Perform exploratory analysis of customer, clickstream, campaign, and transactional data to identify trends, data quality issues, and opportunities for improvement.
• Assist with data validation, monitoring, reconciliation, and troubleshooting across MarTech integrations.
• Support customer identity, segmentation, and personalization data flows.
• Assist senior team members with the implementation and evaluation of new MarTech capabilities.
• Document data pipelines, integrations, data definitions, and operational procedures.
• Use modern AI-assisted development tools and coding agents to improve development, testing, debugging, documentation, and analysis.