Location: Newport Beach, CA | On-site ||| Employment Type: Full-time
Are you ready to lead a marketing transformation through quality assurance and automation? As the Junior Data Engineer (Marketing), you’ll be the driving force behind ensuring the quality and performance of our marketing systems. This role builds the data and automation backbone for TRA’s marketing operations - replacing manual Google Sheet processes, automating data cleaning, and enabling real-time reporting across all campaigns. This role ensures that marketing, analytics, and operations teams have accurate, unified, and data from all sources (radio, digital ads, affiliates, CRM, etc.).
What You'll Do
Build and maintain the unified database
- Develop ETL/ELT pipelines pulling from internal systems and third-party APIs into a centralized warehouse
- Write and optimize SQL for transformations and reporting layers
- Model data so it's consistent and documented across sources
API integration
- Build and test integrations against REST APIs
- Handle authentication, pagination, rate limits, and error handling
- Write tests that catch failures early
Data quality ownership
- Build validation and monitoring to catch missing, duplicate, corrupted, or inconsistent records before they reach a dashboard
- Investigate discrepancies and reconcile against source systems
- Establish reusable automated checks
Deployment and automation
- Set up and maintain CI/CD pipelines
- Deploy and monitor scheduled jobs on cloud infrastructure
- Maintain clean version control and participate in code review
Testing and code quality
- Write unit and integration tests for pipelines, integrations, and internal services
- Maintain and grow test coverage as the codebase expands
- Participate in code review and help keep engineering standards consistent across the team
What You Bring
- Bachelor's degree in Computer Science, Data Science, or a related technical field
- 1+ year of hands-on experience (internships and substantial project work count)
- Proficiency in Python and SQL
- Experience calling, testing, and debugging REST APIs
- Working knowledge of Git
- Working familiarity with AWS and/or Azure
- Understanding of CI/CD and automated deployment
- Strong technical reading comprehension and attention to detail
Nice to Have: PostgreSQL, Supabase, Power BI, FastAPI, Docker, dbt/Airflow, or experience working with LLM APIs. Don't have all of these? No problem — we're happy to help you grow into them.
What We Offer
- Comprehensive health, dental, and vision insurance
- Supplemental benefits like: Life Insurance, flexible spending, and many more...
- 401k with a 4% employer match
Compensation: $80,000 - $85,000 per year, depending on experience
Application Process
Qualified applicants will be invited to complete a brief AI-facilitated interview designed to help us learn more about your experience and qualifications. After the AI interview, a member of our recruiting team will personally review your responses and follow up with next steps if you're selected to move forward. This AI tool is used solely to support our recruiters in the initial screening process -- all final hiring decisions are made by our talent acquisition team.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, pregnancy, age, national origin, disability status, genetic information, protected veteran status, or any other characteristic protected by law. is an Equal Opportunity Employer. We value diversity and encourage all qualified individuals to apply.
Skills Required
- 3+ years of experience in marketing automation, analytics, or data engineering.
- Strong skills in Python, SQL, and data transformation (ETL/ELT).
- Experience with Supabase, BigQuery, or similar modern databases.
- Familiarity with ad platforms, Zapier, and API integrations.
- Exposure to AI/ML tools for reporting, data cleaning, or predictive analysis.
- Excellent analytical and problem-solving skills with attention to data accuracy and automation reliability.
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