PL/SQL Developer

PL/SQL DeveloperSupport application development, database engineering, data integration, analytics enablement, and operational database activities for the GrantSolutions platform. Design, develop, test, maintain, and optimize Oracle database solutions, including PL/SQL packages, procedures, functions, triggers, ETL processes, data migration scripts, and performance-tuned database objects. Collaborate 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. 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. Develop and support Oracle database solutions, including packages, stored procedures, functions, triggers, views, materialized views, and sequences, ensuring high performance, scalability, and maintainability. 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. Develop and support cloud-based data integration, reporting, and analytics solutions using AWS technologies such as Amazon Redshift, Amazon S3, Amazon RDS, and related services. 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. Support CI/CD initiatives, 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 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.Bachelor's degree. Minimum of five (5) years of experience in Oracle database development, database engineering, ETL development, data integration, or related 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. Experience with AWS data and cloud services, including Amazon Redshift, Amazon RDS, Amazon S3, and related analytics and integration technologies. Experience with Matillion ETL or similar cloud-native data integration 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 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, and knowledge management. 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.