Database Architecture Specialist

Job DescriptionAs a Database Architect, you will lead the design and optimization of global data infrastructure.This role requires technical expertise across cloud platforms, along with the ability to architect, scale, and govern complex data systems.Key Responsibilities:Architecting and Managing Data Pipelines: Design and implement scalable, fault-tolerant, and high-performance data pipelines using cloud services like AWS Glue, Azure Data Factory, and Lambda.Designing Global Data Infrastructure: Develop and maintain global data infrastructure across multiple regions, optimizing for latency, availability, and compliance with international data standards.Owning Database Architecture: Own and evolve the architecture of core databases and warehouses, including Snowflake, PostgreSQL, MySQL, DynamoDB, DocumentDB, and MongoDB.Leading Data Migrations: Lead and oversee data migrations between cloud platforms (AWS, Azure), legacy systems, and global regions with minimal downtime and high data integrity.Defining Performance Strategies: Define standards for indexing, query optimization, partitioning, and sharding strategies to support high-throughput and low-latency workloads.Championing Observability: Implement and scale monitoring, alerting, and dashboards via CloudWatch, Azure Monitor, Datadog, or similar tools.Required Skills and QualificationsThis is an ideal role for professionals with:Bachelor's Degree in Computer Science, Engineering, or related field6+ Years of experience working as Data Engineer, Database Engineer, or Cloud Data ArchitectProven hands-on expertise with AWS, especially with Glue, Step Functions, and LambdaStrong Python and SQL skills for workflow development and optimizationExperience designing and maintaining data pipelines (ETL/ELT)Proven data migration experience (cross-cloud or hybrid, with minimal downtime)Hands-on with data orchestration tools (e.g., Glue, Step Functions)Solid experience with at least two database systems among: Snowflake, PostgreSQL, MySQL, DynamoDB, MongoDBExperience with monitoring and observability tools (CloudWatch, Azure Monitor, or Datadog)BenefitsAs a professional in this field, you will have:Advanced English LevelOpportunities for career growth and professional developmentOthersAdditional information about the role includes:Azure experience (Data Factory, Synapse, Functions, Monitor)Infrastructure-as-Code (IaC) tools such as Terraform, CloudFormation, or BicepExperience implementing cost governance frameworks in cloud data environmentsHands-on with data transformation tools (DBT or Coalesce)Deep understanding of performance tuning and scaling optimization for both relational and NoSQL databasesExperience mentoring or guiding engineers in best practicesStrong grasp of data quality and validation frameworksKnowledge of partitioning, indexing, and sharding strategies for performance optimizationExposure to CI/CD pipelines for data engineering projects