The posting
Why you'll love this Nue.io opportunity!
We're looking for a Staff Engineer, Datastores to be the technical lead for every system at Nue that stores, moves, and serves data. You'll set the long-term direction for our datastore platform, own its reliability, performance, and cost, and get it ready for 10x growth, while staying hands-on with the hardest problems. This is not a traditional DBA role, and it's broader than a single engine. Our data layer is polyglot: PostgreSQL on AWS (RDS, NeonDB) runs our multi-tenant transactional workloads, ClickHouse runs analytics and reporting, and caching and streaming systems connect them. As a dedicated datastore lead, you'll decide how these systems fit together, which workloads belong where, and the standards every product team follows. Then you'll lead the move to a highly scalable, highly available architecture. If you want company-wide scope, deep technical ownership, and the chance to build the datastore function from the ground up at a fast-growing SaaS company, this is the role for you.
Responsibilities
Set the datastore strategy — Own the multi-year technical vision and roadmap for Nue's data layer across PostgreSQL, ClickHouse, caching, and streaming, and align engineering leadership behind it. Own the fleet end to end — Be accountable for the reliability, availability, performance, and cost of every production datastore, and define the SLOs, error budgets, and operational standards they're held to. Lead the scale-out architecture — Assess how our multi-tenant data layer needs to grow, choose the right approach (partitioning, read scaling, tenant isolation, sharding, or a different datastore), and deliver it, including tenant placement and online rebalancing where needed, to support 10x growth. Lead the migration to fully managed, highly available PostgreSQL — Define the strategy, testing plan, and rollout for moving off self-managed RDS instances (Aurora/NeonDB), with zero data loss and minimal downtime. Own the analytics data layer — Lead ClickHouse architecture, including table engines, partitioning and ordering keys, materialized views, and the CDC and ingestion pipelines (e.g., Kafka, ClickPipes) that keep it in sync with our transactional systems. Decide what belongs where — Guide product teams on the right datastore and data model for each workload (OLTP, OLAP, cache, queue), and prevent sprawl with clear patterns and paved paths. Make performance proactive — Build the monitoring, alerting, load testing, and capacity models that catch slow queries, replication lag, connection saturation, merge pressure, and storage growth before customers do, and answer "How many more customers can we support?" with data. Architect for resilience — Own replication topologies, read/write separation, failover, backup and restore, and disaster recovery, with RPO/RTO targets that are defined, tested, and met through regular drills. Enable safe, continuous delivery — Establish zero-downtime schema migration practices (backward- and forward-compatible changes, online DDL, migration tooling in CI/CD) that every team uses. Raise the bar across engineering — Review schema and query designs, write the standards and design docs others build on, mentor engineers, and act as a force multiplier for Billing, Lifecycle, Data & Integrations, and DevEx. Secure the data layer — Own encryption in transit and at rest, access controls, secrets rotation, tenant isolation, and audit logging in line with SOC 2 Type II and GDPR. Lead with AI-powered tooling — Use AI throughout the role, from migration planning and query optimization to runbook automation and incident response, and set the example for how the team uses it. Be one of the team — You're a full member of the Infrastructure & Security team, not a specialist on the side. You take your turn on on-call, help ship releases, fix broken CI/CD pipelines, and pick up general infrastructure work when the team needs it, and you lead the response to major datastore incidents. Grow the function — Shape how datastore engineering grows at Nue, including hiring, onboarding, and the operating model as the team scales.
What We’re Looking For
10+ years in backend, infrastructure, or data platform engineering, including 5+ years owning production databases at scale in SaaS environments. A track record of Staff-level impact — you've set technical direction across multiple teams, led multi-quarter initiatives to completion, and aligned senior engineers and leadership around hard trade-offs. Expert-level PostgreSQL — internals (MVCC, vacuum, WAL, the planner), query optimization and EXPLAIN analysis, indexing, partitioning, and replication. Hands-on experience with a columnar/OLAP datastore, ideally ClickHouse (or Druid, Pinot, Snowflake, BigQuery): schema design, ingestion, and performance tuning for analytical workloads. Designed and operated horizontally scaled, multi-tenant database architectures (e.g., partitioning, read scaling, sharding) and replication topologies in production. Led large-scale database migrations with zero data loss and minimal downtime. Deep experience with managed databases on AWS — RDS, Aurora, and/or serverless PostgreSQL (NeonDB, Aurora Serverless v2, Supabase, etc.). Strong observability practice — CloudWatch, pganalyze, HyperDX, Datadog, or similar — including defining and running to SLOs. Solid platform engineering foundations — Infrastructure as Code (Terraform/OpenTofu, CloudFormation), connection pooling (PgBouncer, RDS Proxy), schema migration tooling (Flyway, Liquibase, or similar), and strong scripting (Python, Bash). Deep, hands-on fluency with AI coding agents and developer tools (e.g., Claude, Cursor, Copilot, Codex), with good instincts for where they create leverage. Excellent written and verbal communication — you can write the design doc, explain trade-offs to executives, and build consensus across teams. Team-first and hands-on — you thrive on a small infrastructure team where everyone shares releases, on-call, and pipeline work, and you'd rather fix the broken build than wait for someone else to. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.
Preferred Skills
Experience with in-memory datastores (Redis, Memcached) and streaming/CDC systems (Kafka, Debezium, ClickPipes). Experience with MySQL/MariaDB or NoSQL datastores (e.g., DynamoDB). Experience building internal data platforms or self-service database tooling for product teams. Experience with SOC 2, GDPR, or other compliance frameworks as they apply to data management. Domain knowledge in revenue operations, billing, or financial systems, where correctness and auditability matter. Experience with GitLab CI/CD pipelines. Contributions to open-source database projects, or public talks and writing on database engineering.
What Success Looks Like
A datastore strategy is in place and followed — A roadmap covering PostgreSQL, ClickHouse, caching, and streaming is published, backed by engineering leadership, and used by product teams to decide where new workloads go. The migration to fully managed PostgreSQL is complete — Planned, tested, and rolled out with zero data loss and minimal downtime, replacing self-managed RDS instances. The data layer is ready for 10x growth — A scaling approach is chosen on evidence, documented, and running in production, with clear headroom for 10x customer growth. Analytics scales independently — ClickHouse ingestion, schema, and query performance meet defined SLOs, and analytical load stays off the transactional databases. Reliability is measured, not hoped for — Every critical datastore has SLOs and error budgets, monitoring catches issues before customers do, and DR meets RPO/RTO targets in regular drills. AI is embedded across datastore operations — AI tooling is used every day for migration planning, query optimization, runbook automation, and operations: a force multiplier, not an afterthought. You're the go-to technical leader for data — Product engineering squads (Billing, Lifecycle, Data & Integrations, DevEx) bring you in early on schema design and data architecture, and the standards you set are how Nue builds.
Why You'll Love It
The opportunity to found and lead Nue's datastore function — company-wide scope, high ownership, and direct influence on our architecture. A collaborative and supportive team that invests in your growth, with a clear Staff+ individual contributor path. Flexible remote/hybrid work arrangement within Canada. The chance to work on challenging infrastructure problems at a company scaling rapidly in the revenue lifecycle space.
