Data Engineer - 100% Remote

Largeton Group is a company seeking a Data Engineer for a 100% remote position. The role involves designing, deploying, and managing database solutions on Google Cloud, leading complex data migrations, and optimizing database performance.

Responsibilities:

• Architects & Implements: Designs, deploys, and manages enterprise-grade database solutions using Google Cloud s managed (Cloud SQL - SQL Server, MySQL, PostgreSQL, Oracle etc.) and cloud-native database services (Bigtable, Spanner, AlloyDB, Firestore etc.)
• Migrates Data: Leads complex database migration strategies (homogenous and heterogeneous) from on-premises environments or other clouds to Google Cloud
• Optimizes Performance: Diagnoses and resolves complex database performance issues, optimizes queries, and implements robust backup, recovery, and high-availability (HA/DR) strategies
• Collaborates & Consults: Partners with enterprise customers to understand business requirements and translates them into scalable technical database architectures
• Enforces Best Practices: Establishes security protocols, encryption, and access control policies (IAM) aligned with industry regulations and Google Cloud best practices

Requirements:

• Architects & Implements: Designs, deploys, and manages enterprise-grade database solutions using Google Cloud s managed (Cloud SQL - SQL Server, MySQL, PostgreSQL, Oracle etc.) and cloud-native database services (Bigtable, Spanner, AlloyDB, Firestore etc.)
• Migrates Data: Leads complex database migration strategies (homogenous and heterogeneous) from on-premises environments or other clouds to Google Cloud
• Optimizes Performance: Diagnoses and resolves complex database performance issues, optimizes queries, and implements robust backup, recovery, and high-availability (HA/DR) strategies
• Collaborates & Consults: Partners with enterprise customers to understand business requirements and translates them into scalable technical database architectures
• Enforces Best Practices: Establishes security protocols, encryption, and access control policies (IAM) aligned with industry regulations and Google Cloud best practices
• 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)
• 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