Data Solutions Engineer, Storage

Doordash • New York, NY

240d • $130,600 - $192,000

About The Position

The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering's evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers.

Requirements

• 10+ years of experience designing and scaling distributed data systems, with deep expertise in NoSQL technologies like Apache Cassandra, DynamoDB, or ScyllaDB.
• Strong command of distributed system concepts such as replication, partitioning, tunable consistency, and failure recovery.
• Experience leading data modeling efforts for high-throughput, low-latency workloads and understanding the real-world trade-offs involved in NoSQL schema design.
• Experience with caching technologies like Redis or Memcached and knowledge of how to layer them effectively over storage systems to optimize for performance and cost.
• Customer-first mindset, thriving when working closely with product and platform teams to translate complex requirements into clean, scalable data models.
• Skilled at communicating complex architecture decisions and building alignment across infrastructure and product engineering organizations.
• Track record of mentoring engineers, influencing data architecture at scale, and fostering best practices in reliability, observability, and data access patterns.
• Ability to document decisions, share learnings, and contribute to reusable playbooks and durable frameworks for others to build upon.

Nice To Haves

• Experience working on or contributing to open-source distributed databases.

Responsibilities

• Design and implement highly scalable, fault tolerant distributed database solutions using Taulu, Apache Cassandra, Redis, Kafka, and other paved path storage solutions.
• Architect and optimize multi-region, globally distributed systems to meet our high standards for availability, latency, and throughput.
• Lead data modeling, performance tuning, and capacity planning for large-scale, mission-critical storage workloads.
• Partner with product engineering and infrastructure teams to deeply understand domain specific data needs and guide them in adopting paved path storage solutions.
• Serve as the DRI for solutioning engagements, owning modeling in Taulu from experimentation through launch and scale.
• Shape the evolution of Taulu by identifying abstraction gaps and converting customer feedback into platform improvements.
• Apply workload-aware design patterns, including caching strategies, partitioning, and consistency tuning to improve performance and efficiency.
• Drive adoption of operational best practices across observability, schema design, capacity planning, and cost optimization across storage systems.
• Promote clarity and continuity by contributing to solutioning playbooks, decision logs, and architectural documentation.

Benefits

• 401(k) plan with employer matching
• Paid time off and paid sick leave
• 16 weeks of paid parental leave
• Wellness benefit
• Commuter benefit match
• Medical, dental, and vision benefits
• 11 paid holidays
• Disability and basic life insurance
• Family-forming assistance
• Mental health program

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Industry: Food Services and Drinking Places
• Number of Employees: 5,001-10,000 employees