AI ArchitectAI Data Architect

Noblesoft Technologies

Job Location:

Menlo Park, CA - USA

Monthly Salary: Not Disclosed

Posted on: 6 days ago

Vacancies: 1 Vacancy

Job Summary

Role: AI Architect/AI Data Architect
Location - Menlo Park CA ( Onsite DAY1 ) 4 days WFO

Role Summary: Senior Data Architect/Engineer with 10 years building large-scale AdTech platforms spanning ad serving targeting attribution bidding measurement and real-time analytics. Requires strong Data Streaming Python and Spark skills plus proven experience delivering scalable data systems for Data science/ML workloads.

Key Responsibilities

Lead architecture for batch and real-time AdTech data platforms supporting delivery Ad targeting audience intelligence and analytics.
Design scalable data models and distributed systems for personalization bidding attribution fraud detection and measurement.
Drive engineering decisions across ingestion ETL/ELT streaming storage and Data Science models using Spark Kafka and Python.
Partner cross-functionally to deliver reliable privacy-aware cost-efficient platforms while mentoring teams and guiding technical direction.

Required Qualifications

BS/MS in Computer Science Engineering Data Science or related field.
10 years in software/data/platform engineering with strong AdTech expertise across ad serving targeting bidding attribution and measurement.
Expertise in generating insights experimentation and optimization to characterize performance
Expert in Streaming data Python and Spark; proven success building large-scale distributed data platforms and production-grade data pipelines.
Good understanding of enterprise system architecture
Hands-on with Spark Kafka HBase Hive Presto Flink Airflow/Beam SQL/NoSQL cloud platforms and AI/ML data enablement.

Preferred Qualifications

Experience in digital advertising retail media audience platforms or marketing measurement.
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)
Understanding of Google Ads Scripts or rule-based automation to adjust bids and pause campaigns automatically based on real-time triggers
Exposure to recommendation systems experimentation A/B testing or real-time decisioning.
Knowledge of data privacy frameworks ad-tech regulations Kubernetes Docker and microservices.

Role: AI Architect/AI Data Architect Location - Menlo Park CA ( Onsite DAY1 ) 4 days WFO Role Summary: Senior Data Architect/Engineer with 10 years building large-scale AdTech platforms spanning ad serving targeting attribution bidding measurement and real-time analytics. Requires strong Data ...

Role: AI Architect/AI Data Architect
Location - Menlo Park CA ( Onsite DAY1 ) 4 days WFO

Key Responsibilities

Lead architecture for batch and real-time AdTech data platforms supporting delivery Ad targeting audience intelligence and analytics.
Design scalable data models and distributed systems for personalization bidding attribution fraud detection and measurement.
Drive engineering decisions across ingestion ETL/ELT streaming storage and Data Science models using Spark Kafka and Python.
Partner cross-functionally to deliver reliable privacy-aware cost-efficient platforms while mentoring teams and guiding technical direction.

Required Qualifications

BS/MS in Computer Science Engineering Data Science or related field.
10 years in software/data/platform engineering with strong AdTech expertise across ad serving targeting bidding attribution and measurement.
Expertise in generating insights experimentation and optimization to characterize performance
Expert in Streaming data Python and Spark; proven success building large-scale distributed data platforms and production-grade data pipelines.
Good understanding of enterprise system architecture
Hands-on with Spark Kafka HBase Hive Presto Flink Airflow/Beam SQL/NoSQL cloud platforms and AI/ML data enablement.

Preferred Qualifications

Experience in digital advertising retail media audience platforms or marketing measurement.
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)
Understanding of Google Ads Scripts or rule-based automation to adjust bids and pause campaigns automatically based on real-time triggers
Exposure to recommendation systems experimentation A/B testing or real-time decisioning.
Knowledge of data privacy frameworks ad-tech regulations Kubernetes Docker and microservices.