๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฐ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฎ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฐ-๐ฎ๐ฌ ๐๐ฃ๐)
Experience: 3+ yrs
Location: Chennai, Tamil Nadu, India
Job Type: Full-time
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.
Requirements
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.