We are looking for a strong Database Engineer with deep expertise in PostgreSQL, distributed systems, database internals, and production database operations. The role focuses on designing, scaling, automating, and optimizing database infrastructure for high-throughput, cloud-native environments.

The ideal candidate will have a strong understanding of storage engines, replication, transactions, concurrency, reliability, performance optimization, and data consistency, combined with strong Python skills for building production-grade automation and operational tooling.

Key Responsibilities

• Design, operate, optimize, and scale production database systems across SQL and NoSQL environments.
• Debug and prevent complex concurrency issues, including deadlocks, lock contention, starvation, and long-running transactions.
• Advise application teams on safe database access patterns, including idempotency, retries, backoff strategies, and concurrency controls.
• Develop a deep understanding of database storage and replication internals, including B-trees, LSM structures, page layouts, WAL/redo/undo, checkpoints, compaction, MVCC, and storage engines.
• Design and implement database backup, restore, upgrade, migration, and disaster recovery strategies.
• Analyze query planner behavior, statistics, cardinality estimation, and query performance bottlenecks.
• Develop effective indexing strategies while considering write amplification, storage, and performance trade-offs.
• Build database reliability practices, preventative controls, and automated remediation mechanisms.
• Implement monitoring and alerting for replication lag, lock contention, cache health, slow queries, storage growth, and failover events.
• Lead database incident response, root-cause analysis, and post-incident reviews.
• Build production-grade Python automation and tooling for health checks, failover validation, backup/restore verification, consistency checks, and diagnostics.
• Automate online schema changes, safe rollout and rollback workflows, and operational guardrails.
• Develop automation for performance diagnostics, including query-plan capture and workload analysis.
• Build scalable tooling capable of efficiently processing millions of records or events, with strong attention to time and space complexity.
• Guide data-modeling decisions across relational, document, and key-value databases.
• Evaluate normalization vs. denormalization, secondary indexing, partitioning, hot-spot mitigation, throughput planning, TTL, archiving, and data lifecycle policies.
• Establish standards for data correctness, durability, operational safety, access controls, auditing, and production change management.
• Partner with application and infrastructure teams on database architecture, migration strategies, and operational best practices.
• Contribute to multi-region architectures, failover strategies, and high-availability database solutions where required.
• Mentor engineers and promote strong database engineering practices across the organization.

What Makes You a Great Fit

• 3+ years of relevant engineering experience with strong hands-on database engineering responsibilities.
• Deep expertise in PostgreSQL and strong understanding of at least one additional SQL or NoSQL database such as MySQL, MongoDB, or MariaDB.
• Strong foundation in distributed systems, including CAP, replication, consistency, failure handling, and consensus fundamentals.
• Deep understanding of transactions, isolation levels, MVCC, locking, concurrency, storage engines, and database internals.
• Strong proficiency in Python, with experience building production-grade automation, diagnostics, and operational tooling.
• Hands-on experience operating, troubleshooting, tuning, and scaling production databases.
• Strong debugging and performance-analysis skills, with the ability to reason from metrics, logs, traces, and low-level system behavior.
• Good understanding of Linux and common command-line tools.
• Ability to evaluate technical trade-offs across latency, consistency, durability, throughput, cost, and performance.
• Strong first-principles approach to understanding database behavior under high load and failure conditions.
• Experience designing reliable automation, safe database migrations, and operational guardrails.
• Strong communication and collaboration skills, with the ability to influence application and infrastructure teams.
• Demonstrated ownership, technical judgment, and ability to mentor other engineers.

Nice to Have:

• Experience with multi-region databases, global tables, and cross-region failover.
• Familiarity with AWS, production support, and on-call environments.
• Understanding of networking concepts such as VPCs, subnets, security groups, CIDR, and peering.
• Experience with Kubernetes or self-managed database infrastructure.
• Experience building internal database platforms, self-service tooling, policy-as-code, or safe migration frameworks.