Data Platform Engineer (IC Role – SDE 2 to Staff)

This role involves designing and managing the foundational infrastructure of a data lakehouse, developing real-time stream processing frameworks, and creating self-service ETL and query frameworks. The ideal candidate will have 3-12 years of experience in data engineering, with a focus on building or managing a data platform. They will possess deep hands-on expertise with tools like Spark, Hudi/Delta Lake, Kafka, Airflow, Debezium, Presto/Trino, DBT, and Airbyte, and be comfortable working with the AWS data ecosystem.

Requirements

• Take full ownership of the data lakehouse, including its architecture, ingestion from CDC sources, scalability, and reliability
• Develop and manage real-time stream processing frameworks for applications such as anomaly detection, customer 360 views, and live supply chain signals
• Design and scale OLAP stores to support both real-time and batch processing for internal analytics and AI/ML pipelines
• Create self-service ETL and query frameworks that enable data consumers to operate quickly without creating bottlenecks for the platform team
• Implement cost observability measures that provide detailed insights into compute, storage, and query expenses by job, user, and source
• Build data movement APIs and reverse-ETL pipelines to efficiently deliver data to downstream consumers at scale
• Establish robust job orchestration layers that remain stable under scale

Benefits

• Opportunity to work on a data platform that powers AI for Fortune 500 companies
• High ownership and challenge of working at true scale