Description

• Google Cloud Databases: Hands-on engineering experience deploying and managing native Google Cloud services, specifically Cloud SQL (PostgreSQL/MySQL/SQL Server), Cloud Spanner for globally distributed transactional workloads, Bigtable and AlloyDB for high-performance enterprise workloads.
•  Relational Database Management Systems (RDBMS): Deep technical expertise in core enterprise RDBMS platforms, including PostgreSQL, Oracle, and Microsoft SQL Server (AO AG, Active Directory Integration), with a comprehensive understanding of database engines, schema design, and concurrency controls.
• Enterprise Migration Methodologies: Practical experience executing large-scale, minimal-downtime migrations using tools like Google Cloud Database Migration Service (DMS), Ora2Pg, or similar CDC (Change Data Capture) pipeline technologies for both homogenous and heterogeneous migrations.
• Performance Engineering & Optimization: Mastery of deep-dive performance diagnostics, including the analysis of query execution plans, wait states, indexing strategies, and connection pooling to resolve complex bottleneck issues.
• High Availability & Disaster Recovery: Experience designing and validating robust replication architectures, failover mechanisms, multi-region disaster recovery setups, and point-in-time recovery (PITR) strategies.
•  Infrastructure as Code (IaC) & Automation: Proficiency in provisioning and managing cloud database infrastructure programmatically using Terraform, alongside automation scripts written in Python, Bash, or Go.
• Application Coding: Ability to understand and change code (Database Connectivity Code) in some of the common programming languages like Java, Python etc. Understanding of popular build systems, ORMs and common database libraries (like jdbc, odbc, hibernate).

Nice to Have

•           Google Cloud Certifications: Professional Cloud Database Engineer.

•           Hybrid/Multi-Cloud Experience: Experience managing hybrid data environments or migrating from AWS/Azure to Google Cloud.

•           Data Analytics Integration: Experience tying database infrastructure into modern analytics and pipeline workflows (e.g., Dataflow, CDC).

•           Automation: Strong scripting skills (Python, Bash, or Go) for database automation and monitoring tasks

Key Skills

Education

Bachelor's degree