Ads Data Engineer - HTS Media Services

Ads Data Engineer - HTS Media Services

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HTS Media is Hopper’s advertising and media division, built to help travel brands, destinations, and suppliers connect with travelers  power advertising placements across Hopper’s app and through our B2B partner network, which includes global brands like Capital One Travel and Trip Advisor. Our mission is to build the travel industry’s leading retail media network, turning advertising into a major driver of profitability for Hopper and our partners, much like Instacart, Uber, and Amazon have done in their sectors.

We’re still in the early stages of our roadmap, yet HTS Media has already become one of Hopper’s fastest-growing and most profitable business units. The engineering team plays a pivotal role in scaling the platform, ensuring our ad tech products deliver measurable impact for advertisers and seamless experiences for travelers.

As the foundational Data Engineer for HTS Media, you will own the data infrastructure that powers our entire advertising business. Our platform generates a massive volume of data—from ad impressions and clicks to audience segments and conversion events—that is critical to our advertisers, partners, and internal teams. Your mission is to build a robust, scalable data foundation from the ground up that transforms this raw data into the trusted, high‑quality datasets that power our advertiser‑facing reporting and enable our future ML models.

You will be responsible for the full lifecycle of data, from building real‑time data pipelines to modeling data in our warehouse for analytics and reporting. You will partner closely with backend, full‑stack, and product teams to power fast, accurate, and reliable reporting that will build advertiser trust. You will lay the groundwork for our ML optimization engine, which will drive ad‑serving predictions (like CTR and conversion rates) to make our platform smarter and more performant—mirroring the successful data‑driven ad platforms at companies like Amazon and Instacart.

Your work will be the foundation of our platform’s intelligence and a key factor in our ability to deliver measurable results.

• Own the Data Architecture:
  Design, build, and maintain scalable and reliable ETL/ELT pipelines to process high‑volume advertising data.
• Build the Foundation:
  Develop and manage our analytical data warehouse, establishing it as the single source of truth for all reporting and analytics.
• Enable Insights:
  Create clean, reliable, and performant data models that power our advertiser reporting dashboards, internal analytics, and billing systems.
• Ensure Data Integrity:
  Implement robust data quality checks, monitoring, and alerting to ensure the accuracy and trustworthiness of our data.
• Collaborate and Empower:
  Work closely with the engineering and product teams to define data requirements and deliver the necessary data infrastructure to support new ad products and features.
• Prepare for the Future:
  Build the foundational data systems that will enable future ML‑driven optimizations for audience targeting and performance prediction.

• 4+ years of data engineering experience, with a demonstrated track record of building and maintaining data infrastructure at scale.
• Expert‑level proficiency in SQL and a programming language like Python or Scala for data processing.
• Hands‑on experience with cloud‑based data warehousing solutions (e.g., Big Query, Snowflake, Redshift).
• Proven success building and operationalizing data pipelines using orchestration tools (e.g., SQLMesh, Airflow, dbt).
• Experience with real‑time data streaming technologies (e.g., Google Pub/Sub, Kafka, Kinesis).
• Strong understanding of data modeling concepts and experience designing schemas for analytical workloads.
• Experience with ad tech, retail media, or large‑scale data systems is strongly preferred.
• Excellent communication skills and an ability to collaborate effectively with both technical and business stakeholders.
• A strong sense of ownership and the ability to operate with a high degree of autonomy in a fast‑paced,…