AWS Database Engineer

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Travel Required:

Clearance Required:

The AWS Database Engineer will support application development, database engineering, data integration, analytics enablement, and operational database activities for the GrantSolutions platform. This role requires hands-on expertise with Oracle and PostgreSQL database solutions and AWS database services, tools, and components. Responsibilities include designing, developing, testing, maintaining, migrating, securing, monitoring, and optimizing database solutions using Oracle SQL and PL/SQL, PostgreSQL and PL/pgSQL, 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), and related AWS capabilities.

The AWS Database Engineer will work closely with application developers, architects, DevOps engineers, data engineers, Product Owners, Scrum teams, business stakeholders, and Federal partners to support mission-critical applications and modernization initiatives. The ideal candidate will be a self-starter with strong analytical and problem-solving skills who can quickly understand complex application data models, independently drive solutions, and deliver high-quality database solutions in an Agile environment.

This role will also support AI-enabled engineering initiatives by applying approved AI-assisted development and automation tools to improve productivity, code quality, documentation, testing, troubleshooting, and software delivery outcomes.

What You Will Do

We are seeking a highly motivated AWS Database Engineer with strong Oracle SQL and PL/SQL expertise, PostgreSQL and PL/pgSQL experience, ETL development experience, and required hands-on experience with AWS database services, migration and schema-conversion tools, monitoring, security, storage, and automation components to support application modernization, database development, systems integration, analytics, and operational support activities.

• Design, develop, and support Oracle database solutions, including packages, stored procedures, functions, triggers, views, materialized views, and sequences, ensuring high performance, scalability, and maintainability.

• Develop, enhance, and optimize SQL and PL/SQL code to support application functionality, reporting, system integrations, and business operations.

• Create and maintain database migration scripts, schema updates, release deployment packages, and automated database deployment processes.

• Design, build, and support ETL workflows, data transformation processes, validation frameworks, and batch data processing solutions.

• Analyze and interpret complex data models, database schemas, enterprise data flows, ERDs, and data mappings to support business and application requirements.

• Design, build, configure, administer, and support AWS database and data solutions using Amazon RDS for Oracle, Amazon RDS for PostgreSQL, Amazon Redshift, Amazon S3, AWS DMS, AWS SCT, Amazon CloudWatch, AWS Secrets Manager, AWS KMS, and related AWS services and components.

• Develop, administer, and optimize PostgreSQL solutions on Amazon RDS, including schemas, functions, procedures, triggers, views, extensions, indexing, partitioning, query tuning, parameter configuration, backup and recovery, high availability, and operational troubleshooting.

• Implement and support AWS database migration, replication, and modernization activities across Oracle and PostgreSQL platforms, including schema assessment and conversion, full-load and change data capture workflows, endpoint configuration, data validation, cutover planning, and post-migration verification.

• Configure and operate AWS database monitoring, logging, backup, recovery, high-availability, encryption, credential-management, and access-control capabilities using Amazon CloudWatch, RDS monitoring features, AWS Secrets Manager, AWS KMS, IAM, and related services.

• Build and maintain data integration pipelines using Matillion ETL and other enterprise data integration platforms.

• Troubleshoot and resolve database issues, data quality concerns, application integration challenges, and performance bottlenecks across environments.

• Perform database performance tuning and optimization using execution plans, indexing strategies, partitioning, optimizer statistics, and Oracle diagnostic and monitoring tools.

• Collaborate closely with software engineers, architects, DevOps engineers, and business stakeholders to deliver scalable and reliable data solutions.

• Participate in Agile development activities, including sprint planning, backlog refinement, daily standups, code reviews, sprint reviews, and retrospectives.

• Contribute to DevSecOps and CI/CD initiatives by implementing automated testing, deployment, monitoring, and compliance practices for database solutions.

• Create and maintain technical documentation, including database designs, data mappings, interface specifications, operational procedures, and support guides.

• Develop and support database unit testing, regression testing, data validation testing, and automated test support for SQL, PL/SQL, ETL, and data migration changes.

• Support production operations, release deployments, incident troubleshooting, root-cause analysis, and post-deployment validation for mission-critical database and application components.

• Leverage approved AI-powered development tools to accelerate SQL and PL/SQL development, code review, troubleshooting, documentation, testing, and knowledge-sharing activities.

• Identify and implement opportunities to apply AI and intelligent automation to database development, data engineering, deployment, monitoring, operational support, and engineering productivity.

• Support data governance, security, privacy, and compliance requirements by implementing least-privilege access, auditability, encryption-aware data handling, and controls aligned with Federal standards such as FISMA, NIST, and FedRAMP where applicable.

• Continuously evaluate emerging database, cloud, AI, and data engineering technologies and recommend improvements that enhance platform capabilities and team productivity.

What You Will Need:

• Must be able to OBTAIN and MAINTAIN a Federal or DoD "PUBLIC TRUST"; candidates must obtain approved adjudication of their PUBLIC TRUST prior to onboarding with Guidehouse. Candidates with an ACTIVE PUBLIC TRUST or SUITABILITY are preferred.

• Bachelor’s degree required.

• Minimum of five (5) years of experience in Oracle database development, database engineering, ETL development, data integration, or related software engineering roles.

• Strong experience in Oracle SQL and PL/SQL development, including packages, procedures, functions, triggers, views, materialized views, sequences, complex queries, performance tuning, and Oracle development tools such as SQL Developer and SQL*Loader.

• Proven ability to design, develop, optimize, troubleshoot, and maintain database solutions supporting enterprise and mission-critical applications.

• Experience designing and implementing ETL solutions, data transformation processes, batch processing frameworks, and data migration initiatives.

• Required: Hands-on experience designing, configuring, administering, monitoring, securing, and troubleshooting AWS database solutions using 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), IAM, and related AWS database components.

• Required: Hands-on experience with PostgreSQL and Amazon RDS for PostgreSQL, including SQL and PL/pgSQL development, database administration, performance tuning, indexing, extensions, parameter groups, backup and recovery, high availability, security, monitoring, and troubleshooting.

• Required: Experience implementing AWS database migration and replication solutions, including source and target endpoint configuration, schema conversion, full-load and change data capture tasks, validation, monitoring, troubleshooting, and cutover support.

• Required: Experience applying AWS database operational controls for high availability, backup and recovery, performance monitoring, logging, encryption, secrets rotation, least-privilege access, and infrastructure automation.

• Experience with Matillion ETL or similar cloud-native data integration, orchestration, and data pipeline platforms.

• Strong understanding of relational database architecture, logical and physical data modeling, ERDs, normalization, indexing, query optimization, transaction management, and referential integrity.

• Experience analyzing and supporting complex enterprise application databases, schemas, and data models.

• Experience developing or supporting database unit tests, regression tests, data validation checks, and deployment verification activities.

• Experience supporting production releases, operational incidents, defect triage, root-cause analysis, and post-release validation in enterprise or mission-critical environments.

• Ability to troubleshoot and resolve database, data quality, integration, and application performance issues across distributed environments.

• Experience supporting database and application deployments using CI/CD pipelines, release automation, and DevSecOps best practices.

• Experience working in Agile software development environments utilizing Scrum, Kanban, or similar methodologies.

• Experience using source control and application lifecycle management tools such as Git, GitHub, Bitbucket, GitLab, or Azure DevOps.

• Experience using approved AI-assisted tools or automation practices to support code generation, optimization, testing, troubleshooting, documentation, code reviews, knowledge management, and engineering productivity improvements.

• Understanding of Responsible AI principles, AI governance, cybersecurity, data privacy, and secure AI adoption within enterprise or government environments.

• Familiarity with AI-enhanced SDLC practices, AI-assisted DevSecOps, intelligent automation, and emerging AI engineering patterns.

• Strong analytical, problem-solving, communication, and organizational skills, with the ability to manage competing priorities, work independently or collaboratively, and continuously adapt to emerging database, cloud, and AI technologies.

What Would Be Nice To Have

• Experience supporting Federal Government or large-scale enterprise applications.

• Experience supporting Grants Management, Financial Management, Case Management, Regulatory, or workflow-driven systems.

• Experience with Oracle Data Pump, Oracle GoldenGate, Informatica, Talend, ODI, Liquibase, Flyway, or similar data integration and migration tools.

• Experience with Amazon Aurora PostgreSQL-Compatible Edition, SQL Server, MySQL, or other enterprise database platforms.

• Experience supporting cloud modernization, database migration, or application modernization initiatives.

• Knowledge of Federal data security and compliance practices, including audit logging, least-privilege access, encryption-aware data handling, and security controls aligned with FISMA, NIST, or FedRAMP requirements.

• Experience with data warehousing concepts, dimensional modeling, enterprise reporting, and business intelligence platforms such as Power BI, Tableau, or Amazon QuickSight.

• Experience supporting data pipelines and data platforms used for analytics, reporting, AI, and machine learning workloads.

• Familiarity with AWS cloud-native application and service deployment architectures.

• Oracle certifications preferred, including:

Oracle Certified Professional (OCP)

Oracle Database Administrator Certified Professional

Oracle SQL Certified Associate

• Experience evaluating and adopting emerging AI technologies to improve software engineering productivity, database development, operational efficiency, and modernization initiatives.

• Familiarity with modern AI data architectures, vector databases, retrieval-augmented generation (RAG), AI agents, knowledge management systems, and enterprise AI platforms.

• Experience participating in AI-driven modernization efforts, intelligent automation initiatives, or enterprise data and analytics programs.

• Hands-on experience with AI-powered development tools such as GitHub Copilot, Microsoft Copilot, Amazon Q Developer, Cursor, ChatGPT Enterprise, Claude, Gemini, or similar platforms.