
Required Qualifications
BS/MS in Computer Science, Engineering, Data Science, or related field.
5 8 years in data engineering, software engineering, or platform engineering with strong experience building scalable data pipelines and distributed systems.
Strong proficiency in Spark and Python, with hands-on experience in production-grade data engineering and cloud-based data platforms.
Hands-on with Spark, Kafka, HBase, Presto, Hive Flink, Airflow/Beam, SQL/NoSQL, cloud platforms, and AI/ML data enablement.
Preferred Qualifications
Good-to-have experience in AdTech e.g. Google Ads, digital advertising, retail media, audience platforms, or marketing measurement.
Exposure Data science models, recommendation systems, experimentation, A/B testing, or real-time decisioning.
Knowledge of Data privacy, data governance, Kubernetes, Docker, and microservices.
Ability to interpret performance metrics, conduct A/B testing, and use analytics tools like Google Analytics 4 (GA4) to track user behavior and Return on Ad Spend (ROAS)