Data Engineering Manager
Santa Clara, California$150.2k - $225.2kFull-timePosted 5d ago
About the role
Manager of Marketing Data Engineering within the Marketing Analytics team to build and operationalize the data foundation for advanced analytics, data science, and machine learning across Marketing at AMD.
Responsibilities
- Build and operate scalable marketing data pipelines, transforming data from internal platforms and external sources into reliable, analysis-ready and machine-learning-ready datasets within Snowflake, Databricks, or comparable cloud data environments.
- Develop reusable API integrations and ingestion frameworks to bring together CRM, marketing automation, digital analytics, media, event, partner, and other relevant data, with appropriate controls for incremental updates, schema changes, failures, and reprocessing.
- Design and maintain canonical datasets and shared data models, establishing consistent definitions, identifiers, relationships, and historical views across core marketing entities such as accounts, contacts, leads, campaigns, engagement, spend, and opportunities.
- Engineer datasets for machine learning and data science, partnering with data scientists to develop features, labels, and training, validation, testing, and inference datasets; apply appropriate historical snapshots and point-in-time logic to support reproducibility and prevent data leakage.
- Lead hands-on engineering delivery and continuous improvement, managing priorities and dependencies, reviewing technical designs and code, mentoring engineers, and improving development practices through reusable components, automated testing, and disciplined release management.
- Establish data quality, observability, and operational reliability, implementing automated validation, pipeline monitoring, freshness checks, and controls for schema and data distribution changes; troubleshoot issues and improve pipeline performance, recovery processes, and compute efficiency.
- Partner with Marketing, Analytics, Data Science, Sales Operations, and IT to understand business priorities, translate use cases into data requirements, and align on dataset definitions, delivery expectations, and ownership.
Qualifications
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related technical field. A master’s degree or equivalent advanced experience is preferred.
Skills
Required:SQLPythonSnowflake / DatabricksAPI-based data integrationsData modeling and canonical data modelsCollaboration / communication
Nice to have:Spark or PySparkMLOps / data engineering practices
Benefits
- Benefits described in AMD benefits at a glance.
Last updated Oct 22, 2026. Interested? Apply on the company site.
About AMD
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