Database Reliability Engineer

DraftKings Inc.•Boston, MA

2d•$112,000 - $140,000•Remote

About The Position

At DraftKings, AI is becoming an integral part of both our present and future, powering how work gets done today, guiding smarter decisions, and sparking bold ideas. It’s transforming how we enhance customer experiences, streamline operations, and unlock new possibilities. Our teams are energized by innovation and readily embrace emerging technology. We’re not waiting for the future to arrive. We’re shaping it, one bold step at a time. To those who see AI as a driver of progress, come build the future together. The Crown Is Yours As a Database Reliability Engineer, you'll support the reliability, scalability, and operational excellence of the database infrastructure powering one of the most demanding real time platforms in sports betting and gaming. In this role, you'll combine deep database expertise with software engineering and infrastructure automation to build resilient, self healing systems, improve platform performance, and drive reliability across cloud and on premises database environments.

Requirements

At least 2 years of experience in Database Reliability Engineering, Database Platform Engineering, Site Reliability Engineering, or a related infrastructure engineering role with a strong database focus.
Experience supporting at least one major relational database, preferably Aurora MySQL, along with operational experience working with technologies such as PostgreSQL, MongoDB, ScyllaDB, Aurora, or other managed cloud database services.
Experience building and operating stateful workloads on Kubernetes using technologies such as StatefulSets, Persistent Volumes, database operators, Terraform, Pulumi, FluxCD, ArgoCD, GKE, or EKS.
Hands on software development experience using Go or Python to build automation, platform tooling, Kubernetes controllers, APIs, and infrastructure that reduces manual effort and improves engineering efficiency.
An automation first, data driven mindset with experience improving reliability through observability, monitoring, service level objectives, capacity planning, performance optimization, and self service engineering solutions.
Practical experience using AI tools such as Claude, GitHub Copilot, Cursor, MCP, or similar technologies to improve design, coding, documentation, troubleshooting, and operational workflows while applying sound engineering judgment to validate AI generated outputs.

Responsibilities

Drive database reliability across PostgreSQL, MySQL, MongoDB, Redis, ScyllaDB, Aerospike, and managed cloud services by supporting high availability, replication, partitioning, storage, and connection management.
Build and enhance automation first database platforms by developing Kubernetes operators, infrastructure as code, GitOps workflows, and production quality tooling in Go or Python to automate provisioning, failover, backups, schema migrations, and lifecycle management.
Build self healing, fault tolerant infrastructure and internal tooling that reduces operational toil, improves engineering efficiency, and simplifies day to day database operations.
Optimize database performance and cost across cloud and on premises environments by supporting capacity planning, resource efficiency, storage optimization, workload consolidation, and performance tuning for large scale systems.
Partner closely with application engineering teams to promote safe database practices, including schema reviews, migration strategies, query optimization, connection management, and zero downtime deployment processes.
Leverage AI to improve engineering productivity and database operations through intelligent observability, anomaly detection, root cause analysis, documentation, predictive insights, and evaluation of AI generated code to ensure reliability and security.