Key skills
Data EngineeringSQLPythonCloud Data WarehousingData PipelinesData ModelingReal-time Data StreamingAd Tech ExperienceCommunication SkillsOwnershipCollaborationScalaMachine LearningMLETLELTData WarehousingAnalyticsSnowflakeBigQueryRedshiftKafkaAirflowdbtKinesisPub/SubCommunication
About this role
Hopper is a leading travel platform that powers advertising placements through its B2B partner network. The Ads Data Engineer will own the data infrastructure for HTS Media, building scalable data pipelines and ensuring data integrity to support advertising reporting and future machine learning models.
Responsibilities:
- 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
Requirements:
- 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., BigQuery, 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
- 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, entrepreneurial culture
- Experience with ad tech, retail media, or large-scale data systems is strongly preferred