Lead Data Engineer
On-siteBeaverton, Oregon, United States
Job Summary
Design and deploy scalable data pipelines and architectures that power analytics and AI initiatives across the Consumer Product and Innovation organization. Lead the development of robust data products, including the semantic layer, by partnering with data scientists, analysts, and product managers to translate complex requirements into technical solutions. Mentor junior engineers while championing best practices in coding standards, data governance, and performance optimization. Build and maintain reusable data engineering components that process diverse data sources with consistency and quality, utilizing CI/CD pipelines to automate deployment and testing. Monitor and optimize enterprise-scale data workflows to ensure high availability and reliability.
Required Qualifications
- Bachelor's degree or equivalent combination of education, experience, or training
- 8+ years of experience as a Data Engineer
- strong expertise in Databricks, PySpark, SQL, and Apache Spark
- Hands-on experience with the Databricks Lakehouse Platform
- Medallion architecture
- Delta Lake
- AWS data services (S3, RDS)
- Proven experience leading and mentoring data engineering teams
- strong skills in CI/CD, Git, and DevOps practices
- Experience with data modeling
- ETL/ELT processes
- real-time data processing frameworks (Kafka, Kinesis, or similar)
- cross-functional stakeholder communication
Desired Qualifications
- Knowledge of Generative AI and Machine Learning pipelines and integrating them into production environments
- Databricks certification (e.g., Databricks Certified Data Engineer or Databricks Certified Developer for Apache Spark)
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