Staff Engineer, Datastores
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Job Description
Staff Datastore Engineer leading PostgreSQL and ClickHouse architecture for Nue’s composable revenue platform. Scaling reliable, secure data systems for SaaS growth across Canada.
Responsibilities:
- Set the multi-year datastore strategy and roadmap across PostgreSQL, ClickHouse, caching, and streaming
- Own reliability, availability, performance, cost, SLOs, error budgets, and operational standards for production datastores
- Lead scale-out architecture for the multi-tenant data layer, including partitioning, read scaling, tenant isolation, sharding, tenant placement, and online rebalancing
- Lead migration to fully managed, highly available PostgreSQL with zero data loss and minimal downtime
- Own ClickHouse architecture, table engines, partitioning, ordering keys, materialized views, CDC, and ingestion pipelines
- Guide product teams on datastore and data model selection for OLTP, OLAP, cache, and queue workloads
- Build monitoring, alerting, load testing, capacity models, and proactive performance practices
- Own replication, read/write separation, failover, backup and restore, disaster recovery, RPO/RTO targets, and regular drills
- Establish zero-downtime schema migration practices and migration tooling in CI/CD
- Review schema and query designs, write standards and design documents, mentor engineers, and support Billing, Lifecycle, Data & Integrations, and DevEx
- Own encryption, access controls, secrets rotation, tenant isolation, and audit logging aligned with SOC 2 Type II and GDPR
- Use AI for migration planning, query optimization, runbook automation, and incident response
- Participate in on-call, releases, CI/CD fixes, general infrastructure work, and major datastore incident response
- Grow the datastore function through hiring, onboarding, and operating model development
- Deliver a datastore strategy, managed PostgreSQL migration, 10x growth readiness, scalable analytics, measurable reliability, AI-enabled operations, and company-wide technical leadership
Requirements:
- 10+ years in backend, infrastructure, or data platform engineering
- 5+ years owning production databases at scale in SaaS environments
- Track record of Staff-level impact, including setting technical direction across multiple teams and leading multi-quarter initiatives
- Expert-level PostgreSQL knowledge, including MVCC, vacuum, WAL, planner, query optimization, EXPLAIN analysis, indexing, partitioning, and replication
- Hands-on experience with a columnar/OLAP datastore, ideally ClickHouse
- Experience designing and operating horizontally scaled, multi-tenant database architectures and replication topologies in production
- Experience leading large-scale database migrations with zero data loss and minimal downtime
- Deep experience with managed databases on AWS, including RDS, Aurora, and/or serverless PostgreSQL
- Strong observability practice, including CloudWatch, pganalyze, HyperDX, Datadog, or similar, and defining and running to SLOs
- Infrastructure as Code using Terraform/OpenTofu or CloudFormation
- Experience with connection pooling such as PgBouncer or RDS Proxy
- Schema migration tooling such as Flyway or Liquibase
- Strong scripting skills in Python and Bash
- Hands-on fluency with AI coding agents and developer tools such as Claude, Cursor, Copilot, or Codex
- Excellent written and verbal communication
- Team-first and hands-on approach to releases, on-call, and pipeline work
- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- Preferred: experience with Redis, Memcached, Kafka, Debezium, ClickPipes, MySQL/MariaDB, NoSQL datastores, internal data platforms, SOC 2, GDPR, revenue operations, billing, financial systems, GitLab CI/CD, or open-source database projects
Benefits:
- Flexible remote/hybrid work arrangement within Canada
- Comprehensive health, vision, dental, and life insurance
- Competitive compensation and benefits
- Staff+ individual contributor path
- Growth and leadership opportunities
- Equal opportunity employer
- Accommodations at any stage of the hiring process
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