Roles & Responsibilities:

• Profile, cleanse, and reconcile outage notification data from email/PDF samples, carrier templates, RDS PostgreSQL tables, S3 landing zones, and exported operational datasets.
• Support AI extraction evaluation loops by comparing model output to human-labeled gold data across severity, notification type, service affected, service layer, root cause, lifecycle, carrier type, verification, and state/geography fields.
• Develop SQL queries, Python/pandas analysis scripts, and repeatable QA checks that measure extraction accuracy, completeness, timeliness, duplicates, alert eligibility, and carrier-level data quality.
• Build dashboard-ready datasets and reporting marts for executive dashboards, national heat maps, carrier scorecards, trend summaries, compliance reports, and crisis-center/state-coordinator operational views.
• Partner with the Data Architect on canonical data models, metric dictionaries, lineage notes, source-to-target mappings, row-level security rules, and dashboard acceptance criteria.
• Create and maintain QuickSight, Power BI, Tableau, or equivalent BI artifacts depending on the approved platform, including KPI definitions, filters, drilldowns, and test cases.
• Analyze grant lifecycle and federal operations data where needed, including eRA/PMS exports, SharePoint trackers, NOFO workflow data, SAM.gov/DNP verification outputs, and manually reconciled spreadsheets.
• Support UAT by preparing test data, validating dashboard numbers with stakeholders, triaging data defects, and translating user feedback into backlog-ready analytical requirements.
• Document repeatable runbooks for data validation, dashboard refreshes, exception handling, and production reporting operations.
• Contribute evidence and documentation for federal security, privacy, and ATO reviews, including audit trails, data handling assumptions, and data quality controls.

Required Professional Skills:

• 4+ years of data analyst, BI analyst, or analytics engineering experience supporting operational reporting, data quality, or decision-support systems.
• Strong SQL skills with PostgreSQL or comparable relational databases; able to write joins, aggregations, window functions, QA queries, and source-to-target validation checks.
• Hands-on Python experience for data analysis and automation, including pandas or similar libraries; able to work with CSV, Excel, JSON, email-derived text, and PDF-extracted data.
• Experience with AWS data or analytics services such as S3, RDS, Lambda, Athena, Glue, QuickSight, CloudWatch, IAM, or related cloud-native data services.
• BI/dashboard development experience using Amazon QuickSight, Power BI, Tableau, or a similar platform, including KPI design and stakeholder validation.
• Ability to work with messy, semi-structured, and unstructured data while maintaining disciplined documentation, assumptions, and reproducible checks.
• Understanding of data governance basics: metric definitions, data dictionaries, lineage, access controls, quality thresholds, retention, and privacy-sensitive data handling.
• Strong communication skills with the ability to explain analytical findings to federal program staff, technical teams, PMs, and executive stakeholders.
• Experience working in Agile delivery environments with Jira, sprint planning, backlog refinement, demos, and UAT support

Preferred Professional Skills:

• Federal, HHS, public health, emergency response, grants management, telecommunications domain experience.
• Experience supporting FedRAMP, FISMA, NIST 800-53, HIPAA-adjacent, Section 508, public trust, or ATO documentation activities.
• Exposure to AWS Bedrock or LLM evaluation workflows, especially classification/extraction accuracy testing and human-labeled validation datasets.
• Experience with event-driven data pipelines using SES, SQS, Lambda, Step Functions, EventBridge, API Gateway, or similar services.
• Familiarity with SharePoint, Microsoft 365, Excel-heavy federal workflows, eRA, PMS, SAM.gov, Do Not Pay, OFAC, NORS, or other government system exports/APIs.
• Ability to produce concise executive reporting, carrier scorecards, trend narratives, and analytical briefs from governed datasets