The AWS Database Engineer will collaborate with application developers, cloud architects, DevOps engineers, data engineers, Product Owners, Agile teams, and federal stakeholders to deliver reliable, secure, and high-performing database solutions.
This position also offers opportunities to leverage approved AI-assisted development and automation tools to enhance database engineering, testing, documentation, troubleshooting, and operational efficiency.
Key Responsibilities
Database Development & Engineering
Design, develop, maintain, and optimize Oracle and PostgreSQL database solutions supporting enterprise applications.
Develop complex SQL queries, PL/SQL packages, stored procedures, functions, triggers, views, materialized views, and sequences.
Develop and optimize PostgreSQL SQL and PL/pgSQL code, including functions, procedures, triggers, and database objects.
Analyze complex data models, database schemas, entity relationship diagrams (ERDs), and enterprise data flows.
Perform database performance tuning using execution plans, indexing strategies, partitioning, optimizer statistics, and database diagnostic tools.
Develop and maintain database migration scripts, schema updates, and automated deployment processes.
Troubleshoot database performance issues, data inconsistencies, integration challenges, and production defects.
AWS Cloud Database Engineering
Design, configure, administer, monitor, and maintain cloud-based database solutions using AWS services, including:
Amazon RDS for Oracle
Amazon RDS for PostgreSQL
Amazon Redshift
Amazon S3
AWS Database Migration Service (AWS DMS)
AWS Schema Conversion Tool (AWS SCT)
Amazon CloudWatch
AWS Secrets Manager
AWS Key Management Service (AWS KMS)
AWS Identity and Access Management (IAM)
Configure and optimize PostgreSQL databases hosted on Amazon RDS, including indexing, extensions, parameter groups, performance tuning, and operational troubleshooting.
Implement database backup, recovery, high availability, monitoring, encryption, and access control mechanisms.
Support AWS cloud modernization initiatives involving Oracle and PostgreSQL databases.
Monitor database performance, availability, resource utilization, and operational health across AWS environments.
Database Migration & Modernization
Support database migration and modernization initiatives across Oracle, PostgreSQL, and AWS environments.
Implement AWS DMS and AWS SCT solutions for database migration, schema conversion, and replication.
Configure source and target database endpoints, full-load migration tasks, and change data capture (CDC) processes.
Perform migration assessments, data validation, reconciliation, cutover planning, and post-migration verification.
Identify opportunities to improve database architecture, scalability, performance, and operational efficiency.
ETL, Data Integration & Analytics
Design, develop, and maintain ETL workflows, data transformation processes, and batch processing solutions.
Build and support enterprise data integration pipelines using Matillion ETL or similar technologies.
Develop data validation frameworks and automated data quality checks.
Support data integration between enterprise applications, databases, reporting platforms, and analytics environments.
Collaborate with data engineers and application teams to ensure data accuracy, integrity, consistency, and accessibility.
Support database solutions and pipelines used for analytics, reporting, and AI/ML workloads.
DevSecOps, Automation & Production Support
Support database deployments through CI/CD pipelines and automated release processes.
Collaborate with DevOps teams to implement database deployment automation, monitoring, and infrastructure management practices.
Develop and execute database unit tests, regression tests, data validation tests, and deployment verification activities.
Participate in production deployments, incident resolution, root-cause analysis, and post-release validation.
Implement database security controls, audit logging, encryption, credential management, and least-privilege access.
Maintain technical documentation, database designs, data mappings, deployment procedures, and operational support guides.
Participate in Agile ceremonies, including sprint planning, backlog refinement, daily standups, sprint reviews, and retrospectives.
AI-Assisted Engineering & Continuous Improvement
Leverage approved AI-powered development tools to improve SQL development, code optimization, testing, troubleshooting, and technical documentation.
Identify opportunities to implement AI-assisted automation within database engineering and operational support activities.
Apply responsible AI practices while maintaining data security, privacy, and compliance requirements.
Evaluate emerging database, cloud, and AI technologies to improve engineering productivity and platform capabilities.
Qualifications
Required Qualifications
Minimum of 5 years of professional experience in database engineering, Oracle database development, ETL development, data integration, or related software engineering roles.
Strong hands-on experience with Oracle SQL and PL/SQL, including stored procedures, packages, functions, triggers, views, materialized views, complex queries, and performance tuning.
Experience using Oracle database development tools such as SQL Developer and SQL*Loader.
Required hands-on experience with AWS database services, including Amazon RDS for Oracle, Amazon RDS for PostgreSQL, Amazon Redshift, Amazon S3, AWS DMS, AWS SCT, Amazon CloudWatch, AWS Secrets Manager, AWS KMS, and IAM.
Strong PostgreSQL and Amazon RDS for PostgreSQL experience, including SQL/PL/pgSQL development, administration, indexing, query optimization, performance tuning, backup and recovery, high availability, and troubleshooting.
Demonstrated experience implementing database migrations and replication using AWS DMS and AWS SCT, including schema conversion, endpoint configuration, full-load migrations, CDC, validation, and cutover activities.
Experience implementing AWS database operational controls for monitoring, logging, backup and recovery, encryption, credential management, access control, and infrastructure automation.
Experience designing and implementing ETL workflows, data transformation processes, batch processing, and data migration solutions.
Experience with Matillion ETL or similar cloud-native data integration and orchestration platforms.
Strong understanding of relational database architecture, logical and physical data modeling, normalization, indexing, transaction management, and referential integrity.
Experience optimizing complex database queries and troubleshooting performance bottlenecks.
Experience developing database unit tests, regression tests, data validation processes, and automated deployment verification.
Experience supporting production database environments, incident management, root-cause analysis, and application releases.
Experience with CI/CD pipelines, DevSecOps practices, and database deployment automation.
Experience working in Agile environments using Scrum, Kanban, or similar methodologies.
Proficiency with version control and development tools such as Git, GitHub, GitLab, Bitbucket, or Azure DevOps.
Familiarity with AI-assisted development tools and their application to software engineering, testing, documentation, and troubleshooting.
Understanding of responsible AI, data privacy, cybersecurity, and secure technology adoption in enterprise environments.
Strong analytical, communication, collaboration, and problem-solving skills.
Ability to work independently, manage competing priorities, and collaborate effectively with cross-functional technical teams.
Must be able to obtain and maintain a Federal Public Trust clearance. Candidates with an active Public Trust or federal suitability determination are preferred.
Preferred Qualifications
Previous experience supporting federal government agencies or large-scale enterprise applications.
Experience with federal grants management, financial management, case management, regulatory systems, or workflow-driven applications.
Familiarity with the GrantSolutions platform or similar federal grants management systems.
Experience with Oracle Data Pump, Oracle GoldenGate, Informatica, Talend, Oracle Data Integrator (ODI), Liquibase, Flyway, or comparable migration and integration tools.
Experience with Amazon Aurora PostgreSQL-Compatible Edition, SQL Server, MySQL, or additional enterprise database technologies.
Experience supporting AWS cloud migration, database modernization, and application transformation initiatives.
Knowledge of federal cybersecurity and compliance standards, including FISMA, NIST, and FedRAMP.
Experience with enterprise data warehousing, dimensional modeling, business intelligence, and reporting technologies such as Power BI, Tableau, or Amazon QuickSight.
Familiarity with AWS cloud-native application architectures and deployment patterns.
Oracle certifications such as Oracle Certified Professional (OCP), Oracle Database Administrator Certified Professional, or Oracle SQL Certified Associate.
Familiarity with modern AI data architectures, vector databases, retrieval-augmented generation (RAG), AI agents, and enterprise AI platforms.
Experience supporting AI-driven modernization, intelligent automation, or enterprise analytics initiatives.
Hands-on exposure to AI-assisted engineering tools such as GitHub Copilot, Microsoft Copilot, Amazon Q Developer, Cursor, ChatGPT Enterprise, Claude, Gemini, or similar technologies.
Education: Bachelor’s degree in Business, Engineering, Computer Science, or related field. Masters degree preferred.
Clearance: Ability to obtain and maintain a clearance is preferred.
Location: Hybrid: 2 days per week at REI Systems’ Sterling, VA office.
EEO Statement: REI Systems is an Equal Opportunity Employer
