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About the Role

The MarTech Data & Integration Developer will develop and support data pipelines and integrations powering the marketing technology ecosystem. As MarTech capabilities expand, reliable access to customer and behavioral data is crucial. This role collaborates across application development, data engineering, and analytics to ensure MarTech platforms receive accurate and usable data. It is a hands-on development role for individuals with a foundation in software development, data engineering, analytics, or data science, seeking to grow within a modern MarTech environment.

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.

Requirements

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, Statistics, or a related field, or equivalent practical experience.
1-3 years of experience in software development, data engineering, analytics engineering, data science, or a related technical role.
Strong SQL fundamentals and experience working with relational or analytical datasets.
Experience using Python for data processing, automation, analysis, or software development.
Experience working with Snowflake or another cloud-based analytical data platform.
Basic understanding of ETL/ELT concepts, data pipelines, and data transformation.
Familiarity with REST APIs, JSON, and application integration concepts.
Strong analytical and problem-solving skills.
Ability to learn new technologies and work collaboratively with technical and business teams.

Skills

SQL
Python
Snowflake
APIs
Event streams
Batch data processing
Apache Airflow
REST APIs
JSON
dbt
Kafka
Google Cloud Platform
Salesforce Marketing Cloud
Salesforce Personalization
Customer data platforms
Git
AI-assisted development tools
OpenAI Codex

Experience Level

1-3 years of experience

Education Level

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, Statistics, or a related field, or equivalent practical experience.

Salary/Compensations

$100,000 to $110,000 annually

Benefits

Medical, dental, vision, life, and disability insurance for the associate and eligible dependents
Flexible Spending Account (FSA)
Health Savings Account (HSA)
401(k) retirement savings program
Mental health resources and Employee Assistance Program (EAP)
Paid vacation time
Paid company holidays
Employee discount across our family of brands
Potential eligibility for annual merit-based compensation increases

About the Company

Success in this role means becoming a productive contributor to the data and integration capabilities supporting our MarTech ecosystem. The developer will help improve the reliability and accessibility of customer and behavioral data, reduce manual data processing, support new MarTech integrations, and grow their technical expertise across data engineering, application integration, and analytics.