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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Shared Data Warehouse (SDW) Process Transformation SME - **Company:** Summit Technologies, Inc. - **Location:** Chantilly, VA, United States - **Experience:** Expert - **Salary:** $125,217.0 - $150,932.0 - **Contract:** Permanent contract - **Skills:** Audit Trail, Databases, Data Architecture, Data Validation, Data Governance, Extract Transform Load (ETL), Data Transformation, Data Sharing, Metadata, Performance Tuning, Data Streaming, Unstructured Data, Data Management - **Published:** July 30, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=b4811587db58b607 ## About the Role * Ten (10) years of overall professional experience in the IT or related field. * ETL Process Design and Development * Data Transformation and Integration * Data Quality and Validation * Performance Optimization * ETL Tool Management * Data Governance and Compliance * Documentation and Reporting * Incident Management and Troubleshooting Required Clearance/Certification(s): * Must possess IT-II security clearance or have a current National Agency Check with Local Agency Check and Credit Check (NACLC) at time of proposal submission. * Relevant certification from a nationally recognized technical authority preferred. * DoW Approved 8570 Baseline Certification: Category IAT Level II. ## Description Implements and supports ETL workflows to extract data from Shared Data Warehouse (SDW) mid-tier, transform it into usable formats, and load it into SDW Oracle DB. Create efficient and scalable ETL pipelines to handle large volumes of data. Ensure ETL processes align with business requirements and data architecture standards. Perform complex data transformations to standardize, cleanse, and enrich SDW data from MOCAS for analytical or operational purposes. Integrate SDW data from MOCAS, including structured, semi-structured, and unstructured data formats. Ensure seamless data flow between SDW, MOCAS and systems, applications, and databases. Implement data quality checks and validation rules within ETL processes to ensure accuracy, consistency, and completeness of data. Identify and resolve data anomalies, inconsistencies, and errors during transformation. Collaborate with stakeholders to define data quality standards and metrics. Monitor ETL process performance and identify bottlenecks or inefficiencies. Optimize ETL workflows, queries, and transformations to improve processing speed and resource utilization. Implement best practices for ETL performance tuning and scalability. Manage ETL tools and platforms (ex. Informatica). Configure and maintain ETL environments, ensuring they are secure, reliable, and up to date. Evaluate and recommend new ETL tools or technologies to enhance data transformation capabilities. Ensure ETL processes comply with DoW organizational policies, industry standards, and regulatory requirements (Ex. Managing PII data). Implements data governance practices to maintain data lineage, metadata, and audit trails. Collaborate with data stewards and governance teams to enforce data security and privacy measures. Create and maintain detailed documentation for ETL workflows, data mappings, and transformation logic. Provide regular reports on ETL process performance, data quality metrics, and operational status. 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