Sr. Database Engineer

We're hiring a Senior Database Engineer to design, build, and operate AWS-native, production grade databases. You will own DBA/admin responsibilities, performance tuning, and end-to-end observability of highly available databases (SQL & NoSQL) to ensure reliable, secure, and discoverable data at-scale.

Own installation, configuration, upgrades, backup/restore, HA/DR, capacity planning maintenance, runtime of Aurora/RDS (MySQL/Postgres), Redshift, DynamoDB, and TimescaleDB.

Implement database connection and memory management, lock contentions, deadlock remediations etc. to ensure database scalability and reliability. Perform data validation, de-duplication, and cleanup tasks to maintain integrity.

Partner with Product, and other engineering teams to enable cross-functional software delivery of new/enhanced platform functions, real time and batch, scheduled/ad-hoc data analytics, reporting across use cases.

Perform SQL and NoSQL performance tuning (indexes, query plans, hot partition mitigation, connection/session tuning, auto-vacuum/maintenance) and root cause analysis for latency and throughput issues.

Implement data quality checks, data drift monitoring, and diffing across environments; alert on SLO/SLA breaches.

Build and own end to end monitoring and dashboards using CloudWatch/Prometheus (or equivalent) across storage, and serving layers, to track database health, identify slow queries, and escalate performance issues.

Treat data as code: version controlled pipelines, CI/CD for ETL/ELT, db scripts, stored procedures and automated testing/validation, environment promotion with rollback.

3+ years in data engineering (or equivalent) with deep AWS expertise in building and maintaining production data platforms.

3+ years of proven DBA/admin expertise and experience across RDBMS (Aurora/RDS: MySQL/Postgres; Redshift) and NoSQL (DynamoDB, MongoDB): installation, upgrades, backup/restore, HA/DR, security, maintenance and performance tuning.

3+ years of expertise in production maintenance of distributed databases, across large-scale data lifecycles -including designing, maintaining partitioning, archiving, purging etc.

Working knowledge with Automation and Performance observability tools, to automate anomaly detection, proactive scaling alarms and build self-healing runtime operations tasks.