Database Developer, Senior

LCG•Rockville, MD

2d•Hybrid

About The Position

LCG is seeking a Senior Database Developer to design, implement, optimize, and support enterprise-scale database, data integration, analytics, and reporting environments. The successful candidate will have deep hands-on expertise with Oracle, Microsoft SQL Server, and MySQL, including advanced SQL, T-SQL, PL/SQL, stored procedures, database performance tuning, ETL development, and cross-platform data integration. This role will build and maintain scalable ETL/ELT jobs and automated data pipelines that extract, transform, validate, and load data from multiple business applications, databases, APIs, files, and cloud-based systems. The developer will support batch operations, scheduled workflows, near-real-time integrations, data migrations, and secure database links across Oracle, SQL Server, and MySQL environments. The Senior Database Developer will also develop Power BI datasets, semantic models, reports, and dashboards that consolidate data from multiple application sources and provide actionable operational, programmatic, and executive-level insights. The role requires an ability to design reliable data models, implement data-quality controls, and optimize reporting performance for large and complex datasets. The ideal candidate brings 5–7 years of senior-level experience in enterprise database development, ETL engineering, performance tuning, analytics reporting, and data integration. Experience applying AI capabilities to database operations, data engineering, data quality, analytics, and SQL development is strongly desired. Familiarity with AWS and Azure cloud environments, as well as professional certifications such as Oracle Certified Professional, Microsoft SQL Server Certification, Microsoft Power BI Data Analyst, or relevant cloud/data certifications, is preferred.

Requirements

Bachelor’s degree in Computer Science, Information Technology, Data Engineering, Information Systems, or a related technical field.
Minimum of 5–7 years of hands-on experience in senior-level database development, database administration support, data integration, ETL development, query tuning, and enterprise reporting.
Demonstrated experience supporting enterprise-scale, production database and data environments.
Ability to obtain and maintain a Public Trust clearance.
Expert proficiency with Oracle, Microsoft SQL Server, and MySQL database platforms.
Expert-level knowledge of SQL, T-SQL, and PL/SQL, including procedural and dynamic SQL.
Advanced experience developing and maintaining stored procedures, packages, triggers, functions, views, and database jobs.
Strong experience with query analysis, execution-plan review, troubleshooting, index design, partitioning, performance monitoring, and database optimization.
Strong understanding of relational and non-relational data modeling, schema design, normalization, dimensional modeling, metadata management, and data-governance principles.
Demonstrated experience designing, developing, scheduling, monitoring, troubleshooting, and maintaining ETL/ELT jobs and automated data pipelines in enterprise production environments.
Experience integrating data from multiple application sources, including relational databases, APIs, web services, flat files, spreadsheets, cloud platforms, and third-party systems.
Strong experience with data cleansing, transformation, validation, reconciliation, exception handling, audit logging, and data-quality controls within ETL pipelines.
Experience designing and managing secure database links, data connectors, and cross-platform integrations across Oracle, SQL Server, MySQL, and related systems.
Experience supporting data migrations and data synchronization across heterogeneous enterprise systems.
Strong hands-on experience developing Power BI reports, dashboards, semantic models, datasets, and dataflows using data from multiple applications and database platforms.
Strong proficiency with DAX, Power Query, data modeling, report design, refresh optimization, workspace management, gateways, and row-level security.
Experience creating executive, operational, analytical, and self-service dashboards using data from Oracle, SQL Server, MySQL, and other enterprise sources.
Ability to translate business and operational requirements into meaningful KPIs, metrics, analytical models, and visualizations.
Experience optimizing Power BI datasets and reports for performance, scalability, security, and reliable refresh operations.
Experience with automation, source control, CI/CD pipelines, database deployment tools, test scripts, and release-management processes.
Familiarity with AI, machine learning, generative AI, or AI-assisted development tools applied to database development, data engineering, analytics, reporting, data quality, classification, anomaly detection, or operational monitoring.
Ability to support secure and governed data access for AI and advanced analytics initiatives, including appropriate handling of sensitive, regulated, or personally identifiable information.
Familiarity with using AI-assisted tools to improve SQL development, documentation, troubleshooting, data-quality analysis, or engineering productivity.
Strong understanding of enterprise data security, access controls, encryption, least-privilege principles, data integrity, privacy, and governance.
Experience working with sensitive or regulated enterprise data and implementing appropriate security and data-protection controls.
Strong problem-solving and analytical skills with the ability to troubleshoot complex database, ETL, integration, and reporting issues.
Strong written and verbal communication skills with the ability to communicate technical concepts to both technical and non-technical stakeholders.
Demonstrated ability to collaborate with application developers, architects, data engineers, analysts, security teams, and business stakeholders.
Experience providing technical guidance or mentorship to database developers, data engineers, analysts, or other technical team members.

Nice To Haves

Experience applying AI capabilities to database operations, data engineering, data quality, analytics, and SQL development is strongly desired.
Familiarity with AWS and Azure cloud environments.
Professional certifications such as Oracle Certified Professional, Microsoft SQL Server Certification, Microsoft Power BI Data Analyst, or relevant cloud/data certifications.
Experience with database and data services in AWS and/or Azure, including cloud-hosted databases, storage, ETL/data-integration services, identity and access management, and monitoring.
Professional certification in database development or administration, such as Oracle Certified Professional, Microsoft SQL Server certification, MySQL certification, or equivalent.
Microsoft Certified: Power BI Data Analyst Associate or equivalent Power BI certification.
Certifications or demonstrated experience with Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric, AWS data services, Oracle Data Integrator, SSIS, or other enterprise ETL/data-engineering platforms.
Experience with Microsoft Fabric, Azure Databricks, Azure Synapse, AWS Glue, AWS Redshift, Amazon RDS, Oracle Cloud Infrastructure, or similar cloud data platforms.
Experience building dimensional models, star schemas, data warehouses, data marts, lakehouse architectures, or enterprise reporting layers.
Experience with Python, PySpark, Spark, REST APIs, JSON, XML, Parquet, CSV, or other common data-engineering formats and integration technologies.
Experience supporting healthcare, public-sector, federal, regulated, or data-sensitive environments.
Familiarity with AI governance, responsible AI practices, data lineage, model-data quality, vector databases, retrieval-augmented generation data pipelines, or enterprise AI platform integrations.

Responsibilities

Design, develop, implement, and optimize advanced database scripts using SQL, T-SQL, PL/SQL, Python, shell scripting, and automation tools to support batch operations, scheduled jobs, ETL/ELT workloads, and data integration processes.
Develop, tune, troubleshoot, and optimize high-complexity SQL queries, stored procedures, triggers, views, packages, functions, and database jobs to maximize throughput and reduce query latency across large datasets.
Collaborate with software engineering and architecture teams to model relational and non-relational schemas; create efficient joins, indexes, partitioning strategies, and data-retention approaches; and support application performance requirements.
Develop and maintain scalable ETL jobs and data pipelines that extract, transform, cleanse, validate, reconcile, and load data from enterprise applications, relational databases, APIs, flat files, cloud platforms, and third-party data sources.
Build and support ETL workflows using applicable technologies such as SQL Server Integration Services (SSIS), Azure Data Factory, AWS data-integration services, Oracle Data Integrator, Python-based pipelines, scheduling tools, or comparable enterprise ETL platforms.
Design and maintain secure database links, connectors, and integration patterns across Oracle, SQL Server, MySQL, and other application data sources, enabling reliable distributed data access and near-real-time data retrieval.
Implement and support cross-system data migrations, ensuring accurate, auditable, secure, and efficient movement of data between heterogeneo database platforms and enterprise applications.
Establish data-quality rules, reconciliation processes, exception handling, audit logging, and monitoring for ETL jobs and database processes.
Design data models, staging layers, operational data stores, reporting data marts, and curated analytical datasets that support enterprise reporting, dashboards, ad hoc analysis, and AI/analytics use cases.
Establish scalable data structures and integration approaches that support operational, analytical, and executive reporting requirements.
Ensure data models and analytical datasets are designed for performance, maintainability, data integrity, and reuse across enterprise applications.
Develop Power BI dashboards, reports, dataflows, and semantic models that combine and visualize data from multiple enterprise applications and databases.
Create meaningful KPIs, metrics, drill-through reporting, trend analysis, and executive-ready visualizations.
Use Power Query, DAX, SQL, and data-modeling best practices to prepare and transform data for Power BI reporting.
Optimize Power BI datasets, refresh schedules, gateway connectivity, row-level security, and report performance.
Partner with business stakeholders, data owners, analysts, and engineering teams to define dashboard requirements, translate business questions into measurable metrics, and deliver self-service reporting solutions.
Monitor and troubleshoot Power BI refreshes and related reporting data pipelines to ensure reliable access to current information.
Implement AI-enabled database and data-engineering capabilities, such as intelligent data classification, anomaly detection, data-quality monitoring, metadata enrichment, automated documentation, natural-language-to-SQL assistance, and AI-assisted query or code optimization where appropriate.
Support AI and machine-learning initiatives by preparing high-quality training and analytical datasets, designing secure and governed data-access patterns, and enabling reliable ingestion of structured and semi-structured data from multiple systems.
Evaluate and responsibly apply generative AI and machine-learning tools to improve database development productivity, SQL review, ETL monitoring, data lineage documentation, error triage, reporting insight generation, and operational support.
Oversee and support Oracle, SQL Server, and MySQL database environments, including high availability, backup and recovery, disaster-recovery planning, capacity planning, performance monitoring, and root-cause analysis.
Enforce data integrity, role-based access controls, least-privilege access, encryption, secure scripting practices, and compliance with applicable security, privacy, and regulatory requirements.
Develop automated database deployment, testing, and validation processes using source control, CI/CD pipelines, database migration tools, and scripted release-management practices.
Support production troubleshooting and root-cause analysis for database, integration, ETL, and reporting issues.
Provide technical mentorship to database developers, data engineers, analysts, and application teams.
Champion best practices for SQL development, ETL architecture, dashboard design, data governance, performance tuning, and AI-assisted data operations.
Partner with application developers, architects, infrastructure teams, security teams, analysts, and business stakeholders to ensure database and data solutions align with enterprise requirements.
Maintain appropriate technical documentation for database designs, data models, integrations, ETL processes, reporting solutions, operational procedures, and support activities.