MEMSQL; Singlestore Engineer

We are seeking a highly skilled MemSQL (Single Store) Database Engineer to support large-scale, high-performance data platforms. The ideal candidate will have hands‑on experience with Single Store/MemSQL administration, SQL optimization, distributed database architecture, and real‑time data processing environments.

The candidate will work closely with application teams, data engineers, Dev Ops teams, and business stakeholders to ensure database performance, scalability, reliability, and availability.

• Design, implement, and maintain Single Store (MemSQL) database environments.
• Manage distributed database clusters including Aggregator and Leaf Nodes.
• Monitor database health, performance, and resource utilization.
• Perform query tuning, indexing optimization, and performance troubleshooting.
• Implement backup, recovery, disaster recovery, and high‑availability solutions.
• Support database replication, partitioning, and cluster scaling activities.
• Develop and optimize complex SQL queries, stored procedures, and database objects.
• Work with real‑time and batch data ingestion pipelines.
• Troubleshoot production incidents and database‑related issues.
• Automate database administration activities using Python, Shell scripting, or similar tools.
• Collaborate with Data Engineering and Dev Ops teams for CI/CD deployments.
• Ensure database security, access management, and compliance standards.
• Create and maintain technical documentation and operational runbooks.

• 5–8 years of overall database administration or database engineering experience.
• 3+ years of hands‑on experience with MemSQL / Single Store.
• Strong expertise in SQL development and query optimization.
• Knowledge of:
• Sharding
• Replication
• High Availability (HA)
• Disaster Recovery (DR)
• Experience with Linux/Unix environments.
• Strong understanding of OLTP and OLAP workloads.
• Experience with performance monitoring and troubleshooting.
• Hands‑on scripting experience using Python, Shell, or Bash.
• Strong understanding of database security best practices.

• Experience with cloud platforms such as AWS, Azure, or GCP.
• Experience with Kafka, Spark, Flink, or other streaming technologies.
• Exposure to data warehousing and real‑time analytics platforms.
• Familiarity with monitoring tools such as Prometheus, Grafana, Splunk, or Datadog.
• Knowledge of CI/CD pipelines and Dev Ops practices.
• Experience supporting telecom, network analytics, or large‑scale enterprise applications.

• Bachelor's Degree in Computer Science, Information Technology, or related discipline.
• Strong communication and stakeholder management skills.
• Ability to work in a fast‑paced production environment.

• Big Query exposure.
• Experience with AI/ML data platforms and large‑scale analytics solutions.