Database Engineer, AWS DMS

Overview As a DMS Database Engineer you partner with software engineers and field teams to simplify customer migrations and diagnose complex replication and migration failures. You translate customer pain points into actionable fixes, guiding production incidents involving CDC, schema migration, and data validation across heterogeneous engines. You combine deep database internals with customer-facing problem solving to turn failures into root causes and durable improvements. You work in a fast-paced, cross-functional environment with a strong focus on reliability and automation. Compensation / Benefitshealth insurance401(k) matchingpaid time offparential leaveRSUssign-on payments ResponsibilitiesDiagnose and resolve complex production issues across PostgreSQL, Oracle, SQL Server, MySQL, or DB2 using deep database internals knowledgeInvestigate performance degradation, data corruption, replication lag, CDC failures, and schema migration edge casesBuild automation, log analysis tools, and diagnostic scripts using SQL and scripting languages to accelerate troubleshootingApply knowledge of CDC, logical replication, log-based capture, and data validation to guide migration challengesCollaborate with SDEs on root cause analysis by reasoning about C/C++ or Java code in the DMS replication engineOperate end-to-end within AWS ecosystem (RDS, Aurora, DMS, Redshift, S3, CloudWatch) across infrastructure, networking, and database layersDocument complex findings in root cause analyses, runbooks, and knowledge base articlesDesign and code solutions to drive team efficiency, create metrics, and implement automationParticipate in design discussions, code reviews, and cross-functional communicationContribute in a startup-like environment with ownership and focus on high-impact deliverables Key requirements4+ years of relational database technology experience (e.g., Redshift, Oracle, MySQL, MS SQL)Scripting experience (shell, Python, Perl) and a procedural language for at least one database (PL/SQL, T-SQL)Bachelor's degree in computer science or equivalentExperience in Bigdata architecture or strong analytical, detail-oriented, and communication skillsLinux/RHEL familiarityclear communicationcollaborationproblem-solvingdatabase internals (storage engines, transaction logs, replication mechanisms, query optimization)cross-engine replication and CDClog-based capture and data validation