Database Administrator

๐—ง๐—ต๐—ถ๐˜€ ๐—ฟ๐—ผ๐—น๐—ฒ ๐—ถ๐˜€ ๐—ณ๐—ผ๐—ฟ ๐—ผ๐—ป๐—ฒ ๐—ผ๐—ณ ๐˜๐—ต๐—ฒ ๐—ช๐—ฒ๐—ฒ๐—ธ๐—ฑ๐—ฎ๐˜†'๐˜€ ๐—ฐ๐—น๐—ถ๐—ฒ๐—ป๐˜๐˜€

๐—ฆ๐—ฎ๐—น๐—ฎ๐—ฟ๐˜† ๐—ฟ๐—ฎ๐—ป๐—ด๐—ฒ: ๐—ฅ๐˜€ ๐Ÿญ๐Ÿฐ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ - ๐—ฅ๐˜€ ๐Ÿฎ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ๐Ÿฌ (๐—ถ๐—ฒ ๐—œ๐—ก๐—ฅ ๐Ÿญ๐Ÿฐ-๐Ÿฎ๐Ÿฌ ๐—Ÿ๐—ฃ๐—”)

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.

See also

DevOps jobs by country โ€” openings, pay and top skills โ†’

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