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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Developer - Senior Consultant - **Company:** Guidehouse Inc. - **Location:** McLean, VA, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Amazon Web Services, Amazon S3, Audit Trail, Cloud Engineering, Continuous Integration, Data as a Services, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Identity and Access Management, Interoperability, Meta-Data Management, Performance Tuning, Systems Development Life Cycle, Role-Based Access Control, Enterprise Data Management, Data Logging, Servicebus, Data Lakes, Data Lineage, Apache Kafka, Data Management, Data Pipelines, Databricks - **Published:** August 7, 2026 - **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-3FAB41B567090AD4DC/ ## About the Role * Bachelor's degree is required * Minimum FIVE (5) years of experience in data engineering or ETL development using Informatica or similar enterprise data integration platforms. * Experience building and maintaining data pipelines supporting ingestion, transformation, and curation of structured and semi-structured datasets. * Hands-on experience developing Java-based data services, APIs, or integration layers supporting enterprise data access and interoperability. * Working experience with AWS data platform components (eg, S3, IAM, networking) and familiarity with lakehouse architecture such as Databricks. * Experience implementing production-ready solutions with Embedded data quality validation, monitoring, logging, and error handling patterns. * Familiarity with data governance concepts, including metadata management, lineage, and access controls within regulated environments. * Experience working within Agile and CI/CD-enabled delivery environments supporting secure and repeatable deployments., * Experience modernizing Legacy ETL pipelines into cloud-native or lakehouse-based architectures. * Familiarity with Databricks capabilities (Delta Lake, Unity Catalog) and downstream analytics enablement patterns. * Experience with event-driven or streaming integration patterns (eg, Kafka, Kinesis, EventBridge). * Exposure to enterprise metadata/catalog tools (eg, Informatica EDC, Axon) supporting governed data platforms. * Experience supporting federal data platforms or operating in highly regulated environments with strict security and audit requirements. * Knowledge of secure data access patterns, including RBAC/ABAC, encryption, and audit reporting aligned to FISMA and FedRAMP requirements. ## Description * Design, develop, and maintain data ingestion, transformation, and curation pipelines using Informatica and related ETL tools, enabling consistent delivery of high-quality, analytics-ready datasets across the Data Platform. * Extend and integrate Legacy ETL pipelines into AWS and Databricks lakehouse environments, supporting batch and near Real Time ingestion patterns and improving enterprise data availability and reuse. * Build and support Java-based data services, APIs, and integration layers that enable secure, governed access to curated data for analytics, reporting, and downstream consumption. * Contribute to intake and onboarding activities by supporting requirements analysis, source profiling, and implementation of standardized data integration patterns aligned to defined intake processes and SLAs. * Develop production-ready data pipelines and services that meet defined technical, security, and documentation requirements, supporting controlled promotion into production through established SDLC and CI/CD processes. * Implement data quality validation, transformation logic, and performance optimization to improve pipeline reliability, scalability, and operational efficiency. * Integrate data pipelines and services with AWS components (eg, S3, messaging/streaming services) and Databricks environments to support secure, scalable data movement and platform interoperability. * Support governed data engineering practices by implementing metadata capture, lineage tracking, access control patterns, and audit logging to meet compliance, traceability, and security requirements. ## Related Videos - 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