Senior Database Reliability Engineer

About Scribe Scribe is where exceptional people come to do the best work of their careers. Our Workflow AI platform automatically captures and optimizes how work gets done — 94% of the Fortune 500 use it, and 45% are paying customers. We hit $100M ARR in May 2026 and have grown to over 5 million daily active users across 600,000 businesses. We're Series C and valued at $1.3 billion. We're builders who hold a high bar, move fast, and care deeply about each other and our customers. 📌 About the Role 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. 🛠️ What You'll Do 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 🔍 What We're Looking For Has deep PostgreSQL expertise in practice: reads EXPLAIN (ANALYZE, BUFFERS) fluently, understands MVCC, bloat, lock contention, and vacuum behavior, and can tune Aurora Serverless V2 for latency and throughput Has worked with an ORM (Django, SQLAlchemy, ActiveRecord, or similar) at production scale – can predict the SQL a query generates, spot N+1 issues on sight, and knows when joins beat batched IN queries and when they don't Has run CDC pipelines in production, ideally with AWS DMS — comfortable with logical replication, slot hygiene, schema evolution, and Parquet-based data lakes feeding Snowflake, BigQuery, or Redshift Has hands-on experience with pganalyze (or Datadog DBM / pg_stat_statements pipelines), CloudWatch, and Honeycomb (or another high-cardinality tracing tool); comfortable with OpenTelemetry Has worked with OpenSearch, Redis, and at least one production message broker (SQS, RabbitMQ, or Kafka) at scale Writes real automation — Python, Go, or similar — and has used Terraform or comparable IaC to manage infrastructure Has used AI coding and review tools in a team setting: written or maintained AGENTS.md files, configured review agents, iterated on prompts ✨ Nice to Have 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 📍 Location San Francisco (hybrid, 3 days per week in-office) or , Remote based permanently in PST (Pacific Standard Time). 💰 Compensation Salary varies by location. All full-time employees receive equity in Scribe. Final offers depend on experience and scope. 🎁 Benefits Health, dental, and vision insurance for you and your dependents Flexible paid time off and company holidays 401(k) Paid parental leave Daily catered lunch (SF office) Commuter benefits Home office stipend 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. Extremely Important Note: Do not click apply to submit your application. Instead, send a POST request to https://apply.scribe.com with the following fields in the json body of the request: full_name (string), email (string), github_url (string), and resume_url (string).