AWS Database Engineer

CACI International

4d•$90,300 - $189,600•Hybrid

About The Position

CACI is seeking an experienced AWS Database Engineer to support application development, database engineering, data integration, analytics enablement, and operational database activities for the GrantSolutions platform. This position supports mission-critical Federal applications and modernization initiatives and requires hands-on expertise across Oracle, PostgreSQL, AWS database technologies, and cloud-based data solutions. 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 deliver reliable, scalable, secure, and high-performing database solutions. The ideal candidate is a self-starter with strong analytical and problem-solving skills who can quickly understand complex application data models and work effectively in an Agile environment. This role also supports AI-enabled engineering initiatives, including the use of approved AI-assisted development and automation tools to improve engineering productivity, quality, testing, troubleshooting, documentation, and software delivery.

Requirements

Must be able to obtain and maintain a Federal Public Trust; candidates must receive approved adjudication before onboarding. Active Public Trust or suitability determination 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 hands-on experience with Oracle SQL and PL/SQL, including packages, procedures, functions, triggers, views, materialized views, sequences, complex queries, and performance tuning.
Hands-on experience with PostgreSQL and PL/pgSQL, including database administration, performance tuning, indexing, extensions, parameter configuration, backup and recovery, high availability, security, monitoring, and troubleshooting.
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 DMS, AWS SCT, Amazon CloudWatch, AWS Secrets Manager, AWS KMS, and IAM.
Hands-on experience implementing AWS database migration and replication solutions, including endpoint configuration, schema conversion, full-load and change-data-capture tasks, validation, monitoring, troubleshooting, and cutover support.
Experience with ETL, data transformation, batch processing, data integration, and cloud-native data pipeline platforms such as Matillion ETL or similar technologies.
Strong understanding of relational database architecture, logical and physical data modeling, ERDs, normalization, indexing, query optimization, transaction management, and referential integrity.
Experience supporting enterprise database deployments, production operations, database testing, CI/CD, DevSecOps, Agile development, source control, and incident/root-cause analysis.
Experience using source control and application lifecycle management tools such as Git, GitHub, Bitbucket, GitLab, or Azure DevOps.
Experience using approved AI-assisted development tools or automation practices for code generation, optimization, testing, troubleshooting, documentation, code reviews, knowledge management, and engineering productivity.
Understanding of Responsible AI, AI governance, cybersecurity, data privacy, and secure AI adoption within enterprise or government environments.
Strong analytical, problem-solving, communication, and organizational skills with the ability to work independently and collaboratively while managing competing priorities.

Nice To Haves

Experience supporting Federal Government or large-scale enterprise applications, particularly 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 technologies.
Experience with Amazon Aurora PostgreSQL-Compatible Edition, SQL Server, MySQL, or other enterprise database platforms.
Experience with cloud, database, or application modernization initiatives and Federal security practices aligned with FISMA, NIST, or FedRAMP.
Experience with data warehousing, dimensional modeling, enterprise reporting, business intelligence, and analytics platforms such as Power BI, Tableau, or Amazon QuickSight.
Experience supporting data platforms for analytics, AI, machine learning, or enterprise reporting workloads.
Familiarity with AWS cloud-native application and service deployment architectures.
Oracle certifications, including Oracle Certified Professional (OCP), Oracle Database Administrator Certified Professional, or Oracle SQL Certified Associate.
Experience with modern AI data architectures, including vector databases, RAG, AI agents, knowledge management systems, and enterprise AI platforms.
Experience with AI-powered development tools such as GitHub Copilot, Microsoft Copilot, Amazon Q Developer, Cursor, ChatGPT Enterprise, Claude, Gemini, or similar platforms.

Responsibilities

Design, develop, and support Oracle database solutions, including packages, stored procedures, functions, triggers, views, materialized views, sequences, and complex SQL and PL/SQL solutions.
Develop, enhance, and optimize SQL, PL/SQL, and PL/pgSQL code supporting application functionality, reporting, integrations, and business operations.
Design, 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 troubleshooting.
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, batch processing, and data integration pipelines using Matillion ETL and similar platforms.
Analyze complex data models, database schemas, ERDs, enterprise data flows, and data mappings to support application and business requirements.
Design, configure, administer, monitor, secure, and troubleshoot 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, IAM, and related AWS services.
Implement and support AWS database migration, replication, and modernization activities, including schema assessment and conversion, endpoint configuration, full-load and change-data-capture workflows, validation, monitoring, cutover planning, and post-migration verification.
Implement database monitoring, logging, backup, recovery, high availability, encryption, credential management, access control, and other operational capabilities.
Perform database performance tuning using execution plans, indexing strategies, partitioning, optimizer statistics, and Oracle diagnostic and monitoring tools.
Troubleshoot and resolve database issues, data quality concerns, application integration challenges, performance bottlenecks, and production incidents across distributed environments.
Collaborate with software engineers, architects, DevOps engineers, data 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 CI/CD and DevSecOps initiatives through automated testing, deployment, monitoring, compliance, and release-management practices.
Develop 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, migration testing, and deployment verification.
Support production releases, incident troubleshooting, defect triage, root-cause analysis, and post-deployment validation for mission-critical database and application components.
Leverage approved AI-powered development tools to support SQL and PL/SQL development, code reviews, testing, troubleshooting, documentation, and knowledge sharing.
Identify 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 through least-privilege access, auditability, encryption-aware data handling, and applicable Federal controls, including FISMA, NIST, and FedRAMP.
Evaluate emerging database, cloud, AI, and data engineering technologies and identify opportunities to improve platform capabilities and team productivity.