Data Analyst

This is a fully remote position, open to applicants in Maryland.

📋 Description

• Profile, cleanse, and reconcile outage notification data sourced from email/PDF samples, carrier templates, RDS PostgreSQL tables, S3 landing zones, and exported operational datasets.

• Assist in AI extraction evaluation cycles by comparing model outputs to human-labeled gold data across various parameters including severity, notification type, affected service, service layer, root cause, lifecycle, carrier type, verification, and state/geography fields.

• Create SQL queries, Python/pandas analysis scripts, and standardized QA checks to assess extraction accuracy, completeness, timeliness, duplicates, alert eligibility, and carrier-level data quality.

• Develop dashboard-ready datasets and reporting marts for executive dashboards, national heat maps, carrier scorecards, trend summaries, compliance reports, and operational views for crisis centers and state coordinators.

• Collaborate with the Data Architect on establishing canonical data models, metric dictionaries, lineage documentation, source-to-target mappings, row-level security protocols, and criteria for dashboard acceptance.

• Generate and sustain QuickSight, Power BI, Tableau, or equivalent BI artifacts based on the approved platform, including KPI definitions, filters, drilldowns, and test cases.

• Examine grant lifecycle and federal operations data as needed, covering eRA/PMS exports, SharePoint trackers, NOFO workflow data, SAM.gov/DNP verification outputs, and manually reconciled spreadsheets.

• Provide UAT support by preparing test data, validating dashboard numbers alongside stakeholders, triaging data defects, and converting user feedback into backlog-ready analytical requirements.

• Document repeatable runbooks for data validation, dashboard refresh processes, exception management, and production reporting operations.

• Contribute documentation and evidence for federal security, privacy, and ATO reviews, including audit trails, data handling assumptions, and data quality controls.

⛳️ Requirements

• Over 4 years of experience as a data analyst, BI analyst, or in analytics engineering, with a focus on operational reporting, data quality, or decision-support systems.

• Proficient in SQL with PostgreSQL or similar relational databases; capable of writing joins, aggregations, window functions, QA queries, and conducting source-to-target validation checks.

• Practical experience in Python for data analysis and automation, particularly with pandas or similar libraries; adept at handling CSV, Excel, JSON, email-derived text, and PDF-extracted data.

• Familiarity with AWS data or analytics services such as S3, RDS, Lambda, Athena, Glue, QuickSight, CloudWatch, IAM, or related cloud-native data services.

• Experience in BI/dashboard development using Amazon QuickSight, Power BI, Tableau, or a similar platform, including KPI design and stakeholder validation.

• Ability to manage messy, semi-structured, and unstructured data while ensuring thorough documentation, assumptions, and reproducible checks are maintained.

• Basic understanding of data governance principles: metric definitions, data dictionaries, lineage, access controls, quality thresholds, retention, and handling of privacy-sensitive data.

• Excellent communication skills to articulate analytical findings to federal program staff, technical teams, PMs, and executive stakeholders.

• Experience in Agile delivery environments with Jira, including sprint planning, backlog refinement, demonstrations, and UAT support.

🏝️ Benefits

• Medical and Dental Insurance

• Paid Time Off/Holidays

• 401(k) Retirement Plans with Matching

• Remote Work*

• Paid Training

• Employee Referral Program

• Employee Development Program