This role pays more than
68%
of similar roles. Most pay
$147,200–$208,800
— the shaded band above.
At the midpoint, this role pays about
$197k
versus about
$178k
for comparable roles.
Based on 240 similar postings.
Employer
About DoorDash, Inc
DoorDash, Inc. is an American company operating online food ordering and food delivery. It trades under the symbol DASH. With a 56% market share, DoorDash is the largest food delivery platform in the United States.
DoorDash, Inc currently has
187 open roles
on FindRole.
Listed pay typically runs
$144,800–$212,950
across 166 roles with salary data.
As a Senior Security Data Engineer, you will join the Global Cyber Defense team to manage and optimize multi-terabyte-per-day data pipelines across AWS and GCP environments. You will be responsible for the ingestion, routing, enrichment, and schema management of security telemetry to support detection engineers and threat hunters across three brands. Your daily work involves writing production software in Python, Go, Rust, or Java, managing infrastructure as code via CI/CD pipelines, and modeling data within Snowflake, BigQuery, or Redshift. You will also build AI agents, automated runbooks, and custom SIEM connectors while ensuring high availability for critical security logs. The role requires expertise in tools like Kafka, Cribl, Dataflow, Kinesis, or CloudWatch to solve complex problems regarding log volume, cost control, and query performance within a large-scale security infrastructure.
Manage multi-terabyte-per-day log pipelines across AWS and GCP for ingestion, routing, and enrichment.
Control data volume and costs by filtering noise at the edge while maintaining necessary audit logs.
Model security data and optimize query performance in Snowflake, BigQuery, and Redshift.
Develop production services including custom SIEM connectors, API clients, and automation tools.
Establish and monitor SLOs for log availability and freshness using automated dashboards and alerts.
Manage infrastructure as code and CI/CD pipelines for all security data workflows.
Build AI agents and automated runbooks to accelerate triage and remediation across cloud infrastructure.
Enforce IAM and service account governance for the pipeline's various cloud workloads.
What we're looking for
Experience with 5+ years building and operating high-volume data pipelines at multi-terabyte-per-day scale using tools like Kafka, Cribl, Dataflow, Kinesis, or CloudWatch.
Experience with 4+ years writing production software in Python, Go, Rust, or Java for services and tooling.
Deep hands-on experience with AWS and GCP, including infrastructure as code and CI/CD pipelines on GitHub, GitLab, or Bitbucket.
Strong SQL skills and data modeling expertise in columnar warehouses such as Snowflake, BigQuery, or Redshift.
Proven track record of owning reliability for platforms used by other engineers, including participating in an on-call rotation.
Demonstrated leadership and technical project management across infrastructure, platform engineering, and incident response.
Exceptional written and verbal communication skills with a collaborative mindset.
Familiarity with enterprise SIEMs (Google SecOps, Splunk, Elastic, or CrowdStrike) and container technologies like Kubernetes and Docker is preferred.