Database Performance Engineer

About Us

dot Solved, headquartered in Silicon Valley USA, is a leading global provider of business process automation, modern application engineering, and cloud infrastructure services. dot Solved focuses on enabling digital transformations for small, medium, and large enterprises, in the following industries (but not limited to):
High technology, Energy, Manufacturing, Financial Services, Media & Entertainment, Communications, Retail, Healthcare, and Education.

dot Solved drives digital transformations for enterprises by defining, automating, and optimizing complex business processes for the digital era and engineering modern, data & analytic driven, applications that deliver intended business value. With hundreds of successful implementations and experience in Big Data, ERP, and Supply Chain, dot Solved can guarantee the creation of measurable business value from project engagements leading to accelerated business growth and profitability for customers.

Job Description

Position:
Database Performance Engineer

Location:

Chennai - Onsite/Hybrid

Shift Timing:
Regular IST

Engagement Mode:
Full Time

About the role:

We are seeking an experienced Lead Engineer specializing in database performance engineering to optimize and scale mission-critical MySQL and Postgre

SQL systems. This role focuses on deep query analysis, performance tuning, architecture improvements, and production troubleshooting in high-scale environments. You will work closely with application teams, SREs, and platform engineers to ensure database reliability, efficiency, and scalability in a high-throughput environment.

Key Responsibilities

Deep Query Optimization:
Analyze complex SQL queries and execution plans to identify inefficiencies. You will be responsible for rewriting queries, suggesting architectural changes, and implementing indexing strategies that drastically reduce latency.
System Profiling & Bottleneck Analysis:
Use advanced profiling tools to diagnose issues related to CPU, I/O, locking contention, and memory pressure.
Analyze slow or inefficient queries using tools such as EXPLAIN, EXPLAIN ANALYZE, query plans, and performance schema views
Optimize SQL queries, indexes, schema design, and data access patterns
Identify and resolve performance bottlenecks across application, database, and infrastructure layers
Tune database configuration parameters for optimal performance under varying workloads
Conduct capacity planning and performance benchmarking
Design strategies for scaling databases (sharding, partitioning, replication, read/write splitting)
Implement monitoring and alerting for database performance metrics
Troubleshoot production incidents related to database latency, locks, deadlocks, and resource contention
Collaborate with developers to enforce best practices in query design and ORM usage
Lead performance reviews for new features and schema changes
Document performance guidelines and mentor engineering teams

Required

Skills & Qualifications

7+ years of hands-on experience working deeply with relational databases, specifically MySQL and Postgre

SQL, in high-scale, high-throughput environments.
Mastery of SQL optimization:
Exceptional expertise in query optimization, execution plan analysis, and diagnosing complex bottlenecks.
Deep architectural knowledge:
Profound understanding of indexing strategies, joins, transactions, concurrency control, storage engines, locking behavior, and isolation levels.
Tooling proficiency:
Hands-on experience with industry-standard performance tuning and diagnostic tools (e.g., pt-query-digest, _statements).
Systems-level thinking:
Strong grasp of Linux system performance mechanics (CPU, memory, I/O, network) and how they interact with database engines.
Leadership & execution:
Proven ability to troubleshoot critical production issues under pressure, lead cross-functional technical initiatives, and drive consensus among diverse engineering teams.

Preferred Qualifications

Experience managing and scaling databases across varied environments (Self-Hosted MySQL/Postgre

SQL, AWS RDS/Aurora, GCP Cloud SQL).
Deep theoretical and practical knowledge of database internals and query optimizer behavior.
Strong familiarity with distributed systems, microservices architectures, and the role of No

SQL databases in modern tech stacks.
Proficiency in automation and scripting using languages such as Python or Bash.
A demonstrable track record of architecting and delivering massive-scale database performance improvements in a fast-paced product company.

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