Principal Backend Engineer, Performance, Database

iClosed

. Own the performance and scalability of backend systems and the underlying data layer .

Posted 9/24/2026full-timeRemote • PakistanLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing backend systems for performance and scalability, with a strong focus on data layer management and multi-tenant SaaS products. Proficient in diagnosing and resolving performance issues while ensuring high availability and reliability.

Highest-signal resume keywords

Backend System Performance OwnershipMulti-Tenant SaaS ExperienceRelational Database ExpertiseDocument Database ExpertiseKey-Value Database Expertise

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Performance DiagnosisCaching StrategiesDatabase OptimizationConcurrency ManagementLoad BalancingAPI EfficiencyData Layer Capacity PlanningDesign Document WritingQuery GenerationScalable Service Design

Soft Skills

Problem SolvingCollaborationCommunication

Tools & Technologies

APM ToolsTracing ToolsPublic Cloud Services

Industry Keywords

SaaSData Layer ManagementHigh AvailabilityReliabilityPerformance Metrics

Tech Stack

Tools & technologies

CloudETL

About the role

Key responsibilities & impact

Own the performance and scalability of backend systems and the underlying data layer
Design request flows, synchronous versus asynchronous work, state placement, dependency behavior, and scalable service boundaries
Diagnose latency and performance issues using traces, execution plans, metrics, and evidence
Establish instrumentation, review standards, and regression gates to prevent customer-visible problems
Design strategies for read scaling, write scaling, read/write separation, background processing, real-time updates, traffic spikes, high availability, reliability, search, data growth, safe changes, and API efficiency
Review feature-team architecture proposals
Write design documents and decision records for other engineers to build from
Select and optimize relational, document, key-value, and in-memory data stores based on workload and access patterns
Diagnose execution plans, index costs, lock contention, connection pooling, replica lag, partitioning, document aggregation, shard keys, hot partitions, cache behavior, and dual-write issues
Diagnose latency across the full request path, including ORM-generated traffic, synchronous and ETL latency, and third-party integrations
Own data-layer capacity planning and cost per request alongside latency
Introduce design and query reviews for hot paths and data-layer changes
Define standards for migrations, index justification, and work that must not run synchronously
Instrument data access in application traces
Contribute CI regression gates and production-realistic load testing
Investigate performance for the largest customer accounts and per-tenant behavior
Join the escalation on-call rota once established

Requirements

What you’ll need

5+ years building and operating production backend systems
3+ years with performance and scale as a named part of the job
Experience owning performance for a multi-tenant SaaS product under real load
Evidence of designing systems, including rejected alternatives, accepted tradeoffs, and lessons learned
Specific track record diagnosing a performance problem, identifying its cause, implementing a fix, and measuring results
Ability to reason about caching, replicas, indexes, invalidation, staleness, sharding, partitioning, batching, queue buffering, replica routing, CQRS, queues, workers, orchestration, idempotency, dead letters, WebSockets, SSE, long polling, load balancing, autoscaling, headroom, load shedding, replication, failover, degraded operation, timeouts, backoff, circuit breakers, dedicated search indexes, archival, retention, canary deployments, feature flags, online migrations, logs, metrics, traces, and alerts
Ability to write design documents that teams can implement and executives can follow
Deep experience in at least two of relational, document, key-value, and in-memory stores, with working competence across the others
Relational database expertise including execution plans, composite and partial indexes, index write cost, locking, isolation levels, connection pooling, and replica lag
Document database expertise including embedding versus referencing, shard-key selection, aggregation performance, and working-set sizing
Key-value database expertise including access-pattern modelling, partition keys, hot-partition avoidance, secondary indexes, and capacity cost
Cache expertise including caching patterns, eviction, TTL, and cold-cache or cache-loss behavior
Understanding of consistency boundaries and recognizing when a query problem is an application-design problem
Production ownership in multiple backend languages
Understanding of ORM and ODM query generation
Experience with concurrency, connection and resource management under load
Experience with queue design, including handling consumers that fall behind
Experience using APM and tracing tools for diagnosis
Production experience on a major public cloud, including managed data-service cost behavior
Ability to instrument code for future diagnosis

Benefits

Comp & perks

Full-time, permanent employment
Remote work arrangement
High autonomy and significant technical influence
Opportunity to shape backend architecture and performance standards
Potential future leadership opportunity if the function grows and the candidate wants to lead it