This role is for one of our clients
Industry: Software Development
Seniority level: Associate level
Experience: 3+ yrs
Location: Chennai, Tamil Nadu, India
Job Type: Full-time
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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
