Database Engineer

Database Performance Engineer

Experience: 3 to 5 Years
Location: Bangalore
Employment Type: Full-time

Key Responsibilities

• Analyze and optimize SingleStore and MongoDB workloads for performance, scalability, and reliability.
• Investigate and troubleshoot slow queries, high resource utilization, latency, throughput issues, and database bottlenecks.
• Analyze query execution plans and identify opportunities for query, indexing, schema, and data-model optimization.
• Optimize SQL queries, MongoDB queries, aggregation pipelines, indexes, and database access patterns.
• Work with application engineering teams to identify inefficient database usage patterns and recommend improvements.
• Analyze the impact of data distribution, partitioning/sharding, indexing, joins, aggregations, and query patterns on database performance.
• Perform database performance benchmarking and establish performance baselines.
• Conduct root-cause analysis for database performance issues and production incidents.
• Monitor database health, resource utilization, workload patterns, and capacity requirements.
• Collaborate with database/platform teams on performance tuning and capacity planning.
• Provide technical guidance and best practices to application teams for efficient use of SingleStore and MongoDB.
• Develop and maintain Python scripts and automation for database monitoring, diagnostics, performance analysis, and operational activities.
• Document database performance guidelines, troubleshooting procedures, optimization recommendations, and technical solutions.

Required Skills & Experience

SingleStore

• Strong hands-on experience with SingleStore (formerly MemSQL).
• Good understanding of SingleStore architecture and distributed SQL concepts.
• Understanding of aggregator and leaf nodes and distributed query execution.
• Experience with query optimization and EXPLAIN/query plan analysis.
• Strong understanding of indexing and data distribution.
• Knowledge of sharding/distribution keys and their impact on query performance.
• Understanding of rowstore and columnstore and their appropriate use cases.
• Experience troubleshooting performance issues in high-volume or distributed database environments.

MongoDB

• Strong hands-on experience with MongoDB.
• Good understanding of MongoDB architecture and query execution.
• Experience using explain plans to analyze and optimize queries.
• Strong knowledge of indexing, including compound indexes.
• Experience optimizing MongoDB queries and aggregation pipelines.
• Understanding of MongoDB data modeling and its impact on performance.
• Knowledge of replication and sharding.
• Experience troubleshooting MongoDB performance issues at scale.

SQL & Database Performance

• Strong SQL skills and experience writing and optimizing complex queries.
• Strong understanding of database performance tuning and query optimization.
• Good knowledge of indexes, joins, aggregations, partitioning/sharding, transactions, and concurrency.
• Ability to analyze execution plans and identify database performance bottlenecks.
• Experience working with large datasets and high-throughput workloads.
• Strong analytical and problem-solving skills.

Python

• Good working knowledge of Python.
• Ability to write scripts for automation, monitoring, diagnostics, data processing, and database-related utilities.
• Understanding of Python data structures, functions, exception handling, file processing, and basic scripting best practices.
• Ability to work with APIs and database connectivity from Python is an advantage.

Good to Have

• Experience with Kafka or other event-driven/data streaming technologies.
• Exposure to AWS, Azure, or GCP.
• Experience with database monitoring and observability tools.
• Knowledge of REST APIs and data integration patterns.
• Familiarity with Git and CI/CD practices.
• Experience with other distributed or large-scale databases such as PostgreSQL, MySQL, Cassandra, DynamoDB, etc.
• Experience working in a database/platform engineering environment supporting multiple application teams.