Scribe is where exceptional people come to do the best work of their careers. More than 94% of the Fortune 500 use Scribe to own their specialized intelligence: the unique way their teams work, decide, and get things done. Our Specialized Intelligence platform automatically captures how work happens and turns it into a living asset for people and AI agents.
We're growing fast. Since our founding in 2019, we've reached 7 million users across 600,000 businesses. Based in San Francisco, we're a LinkedIn Top Startup, valued at over $1B, and backed by leading investors. Join us in our mission to transform how people work.
We're hiring a
Senior Database Reliability Engineer to own the reliability, performance, and scalability of Scribe's data tier. Our engineering org is doubling — which means the guardrails, automation, and standards you put in place today will carry a much larger team through the next phase of growth. This is a senior IC role with real ownership: you'll set the bar for how engineers across the company interact with our databases, not just keep the lights on.
Our stack is Django on PostgreSQL (Aurora Serverless V2), OpenSearch, Redis (ElastiCache), SQS, and RabbitMQ, with a CDC pipeline running Aurora to DMS to S3 Parquet to Snowflake. Engineers ship through the ORM, not raw SQL — which makes migration safety, index design, and query review genuinely high-stakes work.
Own database reliability across Aurora, OpenSearch, Redis, and our CDC pipeline — including schema design reviews, migration safety (locks, backfills, concurrent index builds, NOT VALID constraints), and incident response for the data tier
Make the Django ORM a strength at scale: catch N+1 patterns in review, extend
QuerySet conventions and physical schema standards, and build the CI checks and
AGENTS.md scaffolding that encode those standards so they scale beyond any single reviewer
Operate and evolve the CDC pipeline from Aurora through DMS to S3 Parquet to Snowflake – including replication slot hygiene, schema evolution safety, and automated checks that catch migrations likely to break downstream consumers before they ship
Build and improve observability across pganalyze, CloudWatch, and Honeycomb, with Django-side instrumentation that ties slow ORM queries back to specific users, flags, and deploys
Drive multi-AZ resilience within our single-region architecture — Aurora writer/reader placement, failover behavior, RTO/RPO, ElastiCache and OpenSearch AZ topology, RabbitMQ survivability
Build self-service tooling and dashboards that give product and platform teams visibility into their own query footprint, reducing the review burden as the engineering org grows
Contribute to onboarding and knowledge-sharing as a large incoming class of engineers joins — write docs, run internal sessions on "what your ORM query is really doing," and feed that knowledge back into AI review tooling
Deep PostgreSQL expertise in practice: read
EXPLAIN (ANALYZE, BUFFERS) fluently, understand MVCC, bloat, lock contention, and vacuum behavior, and tune Aurora Serverless V2 for latency and throughput
Work with an ORM (Django, SQLAlchemy, ActiveRecord, or similar) at production scale – predict the SQL a query generates, spot N+1 issues on sight, and know when joins beat batched IN queries and when they don't
Run CDC pipelines in production, ideally with AWS DMS — comfort with logical replication, slot hygiene, schema evolution, and Parquet-based data lakes feeding Snowflake, BigQuery, or Redshift
Hands-on experience with pganalyze (or Datadog DBM / pg_stat_statements pipelines), CloudWatch, and Honeycomb (or another high-cardinality tracing tool); comfortable with OpenTelemetry
Work with OpenSearch, Redis, and at least one production message broker (SQS, RabbitMQ, or Kafka) at scale
Write real automation — Python, Go, or similar — and use Terraform or comparable IaC to manage infrastructure
Use AI coding and review tools in a team setting: write and maintained
AGENTS.md files, configure review agents, iterate on prompts
Event sourcing on Postgres, or experience with alternate CDC tooling (Debezium, Fivetran, Airbyte) pgbouncer or RDS Proxy at scale with Django connection handling
Deep Honeycomb usage: SLOs, BubbleUp, Triggers, derived columns
Snowflake from the producer side: staging, Snowpipe, external tables on Parquet
Experience scaling data infrastructure through rapid engineering headcount growth
SOC 2 Type II, GDPR, or similar compliance work
Why you'll love working here
Hard, open problems.
Nobody hands you a finished spec. You'll decide what to build with your PM and designer, then own how it performs.
The reach of a unicorn, the headcount of a startup.
We went from $1M to $100M ARR in under four years, with fewer than 200 people. That means more pie than people: scope grows with your impact. Customers like T-Mobile, LinkedIn, HubSpot, New York Life and Northern Trust run on Scribe, so what you own reaches some of the biggest names in business.
Smart is the floor. Kind is the bar.
Low ego, high standards. We compete as a collective and love to see each other win, and One Team, One Dream is one of the most shouted-out values in #values.
Compensation & Location
San Francisco (hybrid, 3 days per week in-office) or
,
Remote based permanently in PST (Pacific Standard Time).
All full-time employees receive equity in Scribe. Final offers depend on experience and scope.
Healthcare Coverage
Equity
401(k) Plan
Flex Benefit
Commuter Benefits
PTO
Parental Leave
Wellness & Family Support
At Scribe, we celebrate our differences and are committed to creating a workplace where all employees feel supported and empowered to do their best work. Scribe is proud to be an Equal Opportunity Employer.
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