AI Data Engineer

Agency rate - 70/hr - Salary - 160k including 10% VP Location - Menlo Park, CA ( Onsite DAY1 ) 4 days WFO Data Engineer Role Summary: AI Data Engineer with 5 8 years of experience building scalable data pipelines to support Data science models. Requires strong Streaming data and Spark/Python skills, solid experience with distributed data processing, and the ability to deliver reliable data systems for batch and real-time workloads. AdTech experience is a plus. Location: Menlo Park, CA Key Responsibilities Build and maintain batch and real-time data pipelines supporting Data Science, analytics, and operational use cases. Develop scalable data models, ETL/ELT pipelines, and distributed processing jobs across structured and unstructured data. Implement ingestion, transformation, streaming, storage, and data quality solutions using Spark, Kafka, Python, and modern data frameworks. Partner with product, engineering, analytics, and data science teams to deliver reliable, privacy-aware, and cost-efficient data platforms. 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) #J-18808-Ljbffr