scribe - Senior Database Reliability Engineer
Requirements
• 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 • 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 • San Francisco (hybrid, 3 days per week in-office) or, Remote based permanently in PST (Pacific Standard Time).
Responsibilities
• You'll be a key engineer on the data tier - helping design schemas and access patterns that scale, tune Aurora for latency and throughput, and reinforce the standards for how engineers interact with our databases. When a migration script seizes up mid-deploy and writes start queueing behind an ACCESS EXCLUSIVE lock, you're shipping the fix. • Make the Django ORM a strength, not a liability: • Review migrations for safety at scale — locks, backfills, concurrent index builds, NOT VALID constraints • Catch N+1 patterns and missing select_related/prefetch_related in review • Help scale review through automation — contribute to AGENTS.md files and DNA scaffolding that encode our conventions, tune AI review bots (Claude Code, Cursor, etc.) to flag risky migrations and ORM anti-patterns, and iterate on those configs as new failure modes emerge • Contribute to major infrastructure initiatives: • Capacity planning workstreams as traffic and engineering throughput grow • Zero-downtime schema migrations and cutovers • Multi-AZ resilience within a single region — Aurora writer/reader placement, failover behavior and RTO/RPO, ElastiCache and OpenSearch AZ topology, RabbitMQ survivability across AZs • Backups, PITR, failover testing, retention • Operate and extend the CDC pipeline (Aurora → DMS → S3 Parquet → Snowflake): • DMS task tuning, replication slot hygiene on the Postgres side • Schema evolution as Django migrations roll through — so a column drop doesn't silently break the warehouse at 6 AM • Parquet layout and partitioning, reliability of the Snowflake handoff • Build automated checks that flag migrations likely to break downstream consumers • Build tooling and guardrails: • Migration review automation and CI checks for risky patterns • Slow query pipelines fed from pganalyze • Self-service dashboards so teams understand their own query footprint • Support and evolve the rest of the stack: • OpenSearch — index design, sharding, mapping changes, reindexing strategy, Django-side indexing pipelines • Redis — caching patterns, eviction, sizing, Django cache framework, Celery/RQ usage, avoiding hot keys and thundering herds • SQS + RabbitMQ — queue design, DLQs, visibility timeouts, exchange/queue topology, AZ mirroring, consumer backpressure, Celery behavior under load • Mentor and share knowledge — With a large incoming class of engineers, contribute to onboarding docs, tech talks, and written guidance — which double as input for the AI review tooling. Run sessions on "what your ORM query is really doing." Participate in incident response and blameless postmortems for the data tier.
Benefits
• Tier 1 (SF, NYC, Seattle)$170K – $230K • Offers Equity • Tier 2 (Boston, LA, CHI, D.C.)$153K – $207K • Offers Equity • Tier 3 (All others)$145K – $195K • Offers Equity • Upload your resume here to autofill key application fields. • Drop your resume here! • Parsing your resume. Autofilling key fields... • Please Note: To ensure a fair and consistent hiring process, Scribe has established the following application guidelines for all roles: • Please Note: • Candidates may apply to up to two different roles within any six month period. • up to two different roles • six month • If a candidate is not selected for a role, we ask that they wait six months before reapplying to that same role. • six months • These guidelines help us give thoughtful attention to each application and encourage candidates to focus on roles that best match their skills and experience. • or drag and drop here • If you answered yes to the question above, please provide more details. • Decline to self-identify • Hispanic or Latino - A person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin regardless of race. • Hispanic or Latino • White (Not Hispanic or Latino) - A person having origins in any of the original peoples of Europe, the Middle East, or North Africa. • White • Black or African American (Not Hispanic or Latino) - A person having origins in any of the black racial groups of Africa. • Black or African American • Native Hawaiian or Other Pacific Islander (Not Hispanic or Latino) - A person having origins in any of the peoples of Hawaii, Guam, Samoa, or other Pacific Islands. • Native Hawaiian or Other Pacific Islander • Asian (Not Hispanic or Latino) - A person having origins in any of the original peoples of the Far East, Southeast Asia, or the Indian Subcontinent, including, for example, Cambodia, China, India, Japan, Korea, Malaysia, Pakistan, the Philippine Islands, Thailand, and Vietnam. • Asian • American Indian or Alaska Native (Not Hispanic or Latino) - A person having origins in any of the original peoples of North and South America (including Central America), and who maintain tribal affiliation or community attachment. • American Indian or Alaska Native • Two or More Races (Not Hispanic or Latino) - All persons who identify with more than one of the above five races. • Two or More Races • Hispanic or Latino • White (Not Hispanic or Latino) • Black or African American (Not Hispanic or Latino) • Native Hawaiian or Other Pacific Islander (Not Hispanic or Latino) • Asian (Not Hispanic or Latino) • American Indian or Alaska Native (Not Hispanic or Latino) • Two or More Races (Not Hispanic or Latino) • I identify as one or more of the classifications of protected veteran listed above • I am not a protected veteran
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