Join Best Buy’s Ad Serving team to help design, build, and operate a next-generation, machine learning–powered Ad Serving platform. In this role, you’ll be at the core of integrating large-scale data pipelines, real-time model serving, and advanced analytics to deliver optimal, high-performance ad experiences. As a member of the Ad Decisioning team, you will work with other engineering teams across the Best Buy marketing ecosystem to create an integrated, reliable, and scalable system spanning GCP and AWS. Your work will ensure that data flows seamlessly—from ingestion, transformation, and model training to real-time ad delivery decisions. This role is remote eligible, which means you would work virtually from home or another non-Best Buy location. What You’ll Do
- Implement scalable ETL/ELT pipelines to process large volumes of clickstream, behavioral, and ad performance data in real time and batch modes.
- Build and maintain integrations between the Ad Server, ML models, and supporting systems such as UIs, analytics platforms, and reporting databases.
- Work closely with data scientists to operationalize ML models for real-time ad decisioning and bidding.
- Leverage GCP Big Query, Dataflow, Airflow, Pub/Sub, AI Platform and AWS Glue, Kinesis, Lambda, SageMaker, Athena for data ingestion, transformation, and model deployment.
- Architect cloud-native data workflows ensuring high availability, low latency, and fault tolerance.
- Work with the operations team to develop CI/CD pipelines for data pipelines and ML model deployments, enabling fully automated testing and releases.
- Participate in on-call rotation and provide operational support for data pipelines and ML-driven ad serving.
- Anticipate and solve data architecture and integration challenges before they impact production.
Basic Qualifications
- Bachelor’s in Computer Science, Data Engineering; or equivalent combination of relevant professional experience and education
- 3 years of modern development with SQL and distributed data processing frameworks such as Spark
- 3 years of experience diagnosing and resolving complex, production-grade data and/or model serving issues
- 3 years of hands-on cloud experience in GCP or AWS
- 3 years of experience in designing and managing distributed data systems and pipelines
- 2 years of Python experience
- Demonstrated experience collaborating with data scientists, product managers, and operations engineers
Preferred Qualifications
- Experience with high-throughput, real-time Ad Serving systems processing thousands of requests per second
- Strong understanding of ad delivery, targeting, and performance optimization concepts
- Proficiency in data orchestration tools (Apache Airflow, Cloud Composer, Step Functions)