Senior Data Quality and Cloud Analytics Analyst

[]{#docs-internal-guid-da7783dc-7fff-1b61-c81b-fb49a68e7a44} Provide expert-level (SME) technical guidance in the design, architecture, and governance of cloud-based data quality frameworks and advanced analytics pipelines supporting federal government data management, statistical, and data analysis support. Advanced Cloud Data Architecture and Pipeline Engineering - Design, architect, and deploy end-to-end cloud-native data pipelines on AWS using services including S3, Glue, Lambda, Athena, and EventBridge to analyze, transform, and deliver large-scale federal program datasets for analytical and reporting use cases. Design cloudenabled analytical data models, semantic layers, and reporting pipelines that integrate cloud and onpremise data warehouse environments for consumption in MicroStrategy and Tableau dashboards. Architect event-driven processing frameworks using AWS Lambda and EventBridge to automate data quality triggers, anomaly alerts, and pipeline monitoring at scale, reducing manual intervention and improving response time to data integrity incidents. Senior Data Quality Framework Design and Governance - Design and implement enterprise-grade data quality frameworks incorporating automated validation rules, statistical threshold monitoring, and exception-handling logic across Oracle, SQL Server, and PostgreSQL environments using PL/SQL, Python, and Unix Shell Scripting. Guide the development of ERD data modeling tools and canonical data schemas to standardize data structures across federal program datasets, enabling cross-program consistency and audit traceability. Establish and document data governance standards, including data dictionary specifications, metadata management, lineage documentation, and data quality certification protocols, to support program-wide trusted data delivery. Advanced Statistical and Predictive Analytics - Design and execute complex, enterprise-grade statistical analyses, predictive models, and forecasting routines using Python, SAS, SQL, and cloudnative analytics platforms to generate insights that inform federal program evaluation, operational decisionmaking, and modernization strategies. Identify, select, and extract the datasets required to support each analytical effort. Develop and maintain analytical models and predictive validation algorithms to proactively identify risks of data quality degradation before dataset delivery, providing probabilistic assessments of reliability and completeness. **Acting as an SME and Cross-Functional Coordination - **Serve as the senior technical point of contact for data quality and cloud analytics issues, providing expert guidance to junior analysts and cross-functional project teams on methodology, toolset selection, and quality assurance approaches. Review and approve technical deliverables, including test plans, data validation scripts, and analytical reports produced by junior team members before submission to federal program stakeholders. Other similar professional duties as assigned. ::: {dir="ltr"} Special Requirements: Experience must be in supporting federal government data management, including data quality, statistical, and data analysis support using: Oracle, PL/SQL, SQL Server, PostgreSQL, MicroStrategy, Tableau, SAS, AWS (S3, Glue, Lambda, Athena, EventBridge), Python, Unix Shell Scripting, and ERD data modeling tools. ::: Requires -[ ]{#docs-internal-guid-f673851b-7fff-89d7-24cd-dbfb7a59459c} A Bachelor's degree in Electronic Engineering, Computer Science, or equivalent, with 6 years of experience in the job offered or any occupation in which the required experience was gained OR a Masters degree in Electronic Engineering, Computer Science, or equivalent, with 4 years of experience in the job offered or any occupation in which the required experience was gained.