Senior Database Support Engineer

Role overview

Database operations and incident support

• Provide database support across MySQL, PostgreSQL, MongoDB, and Couchbase environments.
• Handle Level 2 production escalations, lead root cause analysis, and drive corrective and preventive actions.
• Install and configure MySQL InnoDB and NDB Cluster; maintain replication and resolve replication issues.
• Monitor health, performance, capacity, and availability; tune configurations and analyze workloads.
• Review database changes across Dev, Test, Pre-Production, and Production under change management procedures.

Data platforms, security, and continuity

• Review schema changes, stored procedures, functions, and triggers; advise on query and indexing optimization.
• Support MinIO/S3-compatible storage, including bucket management, access policies, lifecycle rules, and pipeline and archival integration.
• Support lakehouse environments using relational databases, object storage, and query engines for ingestion, transformation, and archival workloads.
• Implement database access, privilege, authentication, and encryption controls; perform audits, integrity checks, and access reviews.
• Execute and validate backup and recovery procedures and support business continuity and disaster recovery planning and testing.
• Maintain configurations, procedures, change records, and operational runbooks.

Qualifications and experience

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• 6+ years of combined database development and/or database support experience.
• Strong proficiency developing stored procedures, functions, triggers, and ETL processes; expertise maintaining databases in production and non-production environments.
• Expertise in MySQL and PostgreSQL, and in MongoDB or Couchbase; expertise implementing and managing Redis caching.
• Hands-on MinIO or S3-compatible object storage experience, including IAM access policies, lifecycle rules, and archival integration.
• Knowledge of lakehouse concepts and tooling, including Apache Iceberg or Delta Lake, Dremio, Trino, Apache Spark, or metadata catalogues such as Project Nessie.
• Experience with big data technologies such as Hadoop or Spark; knowledge of data warehouses, performance tuning, and backup and recovery.
• Knowledge of Python or JavaScript; strong problem-solving, troubleshooting, teamwork, and communication skills.