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Build and maintain scalable data pipelines and metrics for DoorDash’s logistics operations, partnering with engineers and analysts to deliver trusted, self-serve analytics using SQL, Python, and tools like Snowflake and Tableau.
Build and scale data pipelines, ETL workflows, and warehouse models to power analytics and reporting at DoorDash.
Build and scale data pipelines, warehouses, and models to power analytics and reporting at DoorDash, using Python/Java, Spark, Kafka, Airflow, and cloud data platforms.
Builds and maintains DoorDash’s scalable data platform (Spark, Flink, Kafka, Airflow) to enable real-time analytics, data governance, and business insights for logistics/delivery operations.
Build and scale high-performance data pipelines and warehouse models to power analytics and reporting at DoorDash, using Python/Java, Spark, Airflow, Kafka, and Snowflake.
Lead the design and scaling of DoorDash’s data infrastructure, building reliable pipelines and models for analytics, reporting, and financial systems using Python/Scala, Spark, Airflow, and streaming tech.
Build and maintain scalable data pipelines and metrics that power analytics across DoorDash’s operations, using SQL, Python/Scala, and ETL tools to deliver trusted insights for business teams.
Build and scale DoorDash’s in-house Apache Spark platform, optimizing runtime, shuffle service, and Kubernetes-based scheduling to power data, analytics, and ML workloads at massive scale.
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