Senior Lead Database Reliability Engineer

DraftKings Inc.

Senior Lead Database Reliability Engineer enhancing reliability and scalability of database infrastructure at DraftKings, focusing on high availability and performance optimization.

Posted 7/17/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $168,000 - $210,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Database Reliability Engineering with a focus on PostgreSQL and operational experience in various database technologies. Proven ability to design automation-first database platforms, optimize performance, and lead engineering teams towards operational excellence.

Highest-signal resume keywords

Database Reliability EngineeringPostgreSQL ExpertiseKubernetes Workload ManagementAutomation in Go or PythonAI Tools Utilization

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Database Reliability EngineeringPostgreSQLMySQLMongoDBRedisKubernetesGoPythonTerraformPerformance Optimization

Soft Skills

LeadershipCommunicationMentoringCollaborationContinuous Improvement

Tools & Technologies

Kubernetes OperatorsGitOpsAI ToolsTerraformPulumiFluxCDArgoCDGKEEKSObservability Tools

Industry Keywords

Database Platform EngineeringSite Reliability EngineeringService Level ObjectivesCapacity PlanningHigh AvailabilityReplicationStorage OptimizationSchema MigrationsProduction IncidentsCloud Database Services

Tech Stack

Tools & technologies

CloudGoKubernetesMongoDBMySQLPostgresPythonRedisSQLTerraform

About the role

Key responsibilities & impact

Drive the technical roadmap for database reliability across PostgreSQL, MySQL, MongoDB, Redis, ScyllaDB, Aerospike, and managed cloud services, while shaping architecture for high availability, replication, partitioning, storage, and connection management
Design and build 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
Lead operational excellence by defining service level objectives, monitoring database health, capacity, and performance, eliminating recurring reliability issues, validating backup and recovery processes, and leading critical production incidents through resolution and continuous improvement
Optimize database performance and cost across cloud and on premises environments by driving capacity planning, resource efficiency, storage optimization, workload consolidation, and performance tuning for large scale systems
Partner closely with application engineering teams to establish 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
Mentor engineers across the organization by sharing best practices, leading design and code reviews, influencing technical direction, supporting hiring efforts, and raising the overall maturity of database reliability engineering.

Requirements

What you’ll need

At least 6 years of experience in Database Reliability Engineering, Database Platform Engineering, or Site Reliability Engineering with a strong database focus
Deep expertise in at least one major relational database, preferably PostgreSQL, along with operational experience supporting technologies such as MySQL, MongoDB, Redis, ScyllaDB, Aerospike, Aurora, Cloud SQL, and other managed cloud database services
Strong experience building and operating stateful workloads on Kubernetes using technologies such as StatefulSets, Persistent Volumes, database operators, Terraform, Pulumi, FluxCD, ArgoCD, GKE, and EKS
Hands on software development experience using Go or Python to create automation, platform tooling, Kubernetes controllers, APIs, and infrastructure
A data driven, automation first mindset with proven 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
Excellent leadership and communication skills with a track record of mentoring engineers, influencing architectural decisions, collaborating across engineering teams, producing clear technical documentation, and driving continuous improvement in highly available production environments.

Benefits

Comp & perks

plus bonus
equity
benefits as applicable