Data Management / Analytics Lead

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Description

DSFederal is seeking a Data Management / Analytics Lead to direct the data and reporting workstream of a government agency. The Lead provides data and builds automated processes and interfaces for Government business needs, with systems both inside and external, and is accountable for the integrity of the data sent to external entities.

Requirements

• Design, develop, and maintain Talend ETL jobs loading the Enterprise Data Warehouse, integrating data from Source, Staging, and Master schemas into the Reporting schema.
• Modify ETLs, applications, and data processes for changes in source systems and in business rules; refactor logic no longer pertinent.
• Integrate data from new internal and external sources into the Enterprise Data Warehouse and enhance data integration processes.
• Design and maintain data models for the warehouse and reporting schema, including data dictionaries, source-to-target mappings, and lineage documentation.
• Enhance reporting capabilities and processes, business, and infrastructure changes.
• Build automated data extracts, feeds, and interfaces for Government initiatives and external partners; enforce data integrity through validation, reconciliation, and audit controls.
• Establish data quality practices – profiling, reconciliation reporting, and exception handling – and report data quality metrics.
• Protect PII through encryption, masking, and least-privilege access in ETL and reporting pipelines.
• Tune ETL, SQL, and report performance; troubleshoot load failures and data discrepancies.
• Lead and mentor data engineers and analysts; conduct design and code reviews and set data standards.
• Provide workstream input for Weekly/Monthly Status Reports, the IMS, and the Risk Register; brief Government stakeholders and translate data into actionable insights.
• Ensure dashboards, reports, and data products conform to Section 508 / WCAG Level A/AA; follow ITSD change management for deployments.
• Support knowledge transfer, documentation handoff, and Transition-Out activities.

Experience Required

• Minimum 10 years of experience in data management, data warehousing, ETL development, and BI/reporting, including at least 3 years leading data teams or workstreams.
• At least 5 years designing and building ETL with Talend Data Integration (strongly preferred) or a comparable tool (Informatica, Oracle Data Integrator, SSIS).
• At least 7 years of Oracle SQL and PL/SQL; experience with MySQL and SQL Server.
• Experience designing layered data warehouses (source/staging/master/reporting) and dimensional models.
• Experience with federal grants, award, or financial data; familiarity with SAM.gov, ASAP, or Grants.gov data preferred.
• Proven ability to translate data into actionable insights and to communicate findings to executives and program staff.
• Bachelor’s degree in Computer Science, Information Systems, Data Science, Statistics, or a related field; Master’s degree preferred.
• Must be a U.S. Citizen, Lawful Permanent Resident, or valid work-visa holder (per RFQ), and able to obtain and maintain a Public Trust (Moderate Risk or higher) background investigation (minimum NACI), fingerprinting, and an HSPD-12 PIV credential. Must complete annual Information Security Awareness (ISA) and Rules of Behavior (ROB) training.

Technical Skills Required

• ETL: Talend Data Integration 7.x (job design, tMap, context variables, joblets, scheduling, error handling, Java routines).
• Databases: Oracle Database 19c (PL/SQL, partitioning, materialized views, analytic functions, performance tuning), MySQL 5.7, SQL Server.
• Data Modeling: Relational and dimensional (star/snowflake) modeling; tools such as SQL Developer Data Modeler or ERwin; metadata and data dictionaries.
• Reporting & BI: Oracle APEX reporting, Oracle Reports; Google Analytics; Power BI or Tableau a plus.
• Integration: REST/SOAP APIs, flat-file and SFTP/Connect:Direct transfers, XML/JSON/CSV.
• Scripting & Platform: Python and shell scripting on Red Hat Enterprise Linux 8; OpenJDK 8; Redis awareness.
• Data Governance & Security: Data quality frameworks, reconciliation, PII masking and encryption (e.g., DBMS_CRYPTO).
• Tools: JIRA, Confluence, Remedy, Git, Subversion, SharePoint.