Data Analyst

Dynanet Corporation

$70K — $95K *
US-AnywhereRemote in Maryland, US
Information Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 4+ years of experience in data analysis, business intelligence, or analytics engineering
  • Strong SQL skills with experience in PostgreSQL or similar relational databases
  • Hands-on Python experience for data analysis using libraries like pandas
  • Familiarity with AWS data or analytics services such as S3 and QuickSight
  • Proficiency in BI/dashboard development with tools like Power BI or Tableau
  • Experience working in Agile environments with tools like Jira
  • Knowledge of data governance practices and documentation requirements

Responsibilities

  • Profile, cleanse, and reconcile outage notification data from various data sources
  • Support AI extraction evaluation by comparing model outputs with human-labeled data
  • Develop SQL queries and Python scripts for QA checks on data quality
  • Build dashboard-ready datasets for executive reporting and operational views
  • Collaborate with Data Architect on data models and metric definitions
  • Create BI artifacts using QuickSight, Power BI, or Tableau according to approved platforms
  • Document repeatable processes for data validation and dashboard operations

Benefits

  • Industry Competitive Compensation
  • Medical and Dental Insurance
  • Paid Time Off/Holidays
  • 401(k) Retirement Plans with Matching
  • Remote Work
  • Paid Training
  • Employee Referral Program
  • Employee Development Program
Full Job Description
Location: Remote, MD
Posted: 06/09/2026

Position Details:

Job Title: Data Analyst

Job Type: Full-Time / Contracting

Location: Remote

About the Role:

Dynanet is seeking a Data Analyst to support modernization work focused on the outage reporting. The analyst will convert fragmented operational data, unstructured carrier notifications, system exports, and stakeholder reporting needs into governed datasets, dashboard-ready metrics, quality checks, and decision-support products.

The role is intended to augment the project Data Architect and technical team. It is not a passive reporting position; the analyst must be comfortable profiling messy data, writing SQL and Python, validating AI-extracted fields, building BI datasets, documenting metric definitions, and helping federal stakeholders trust the data before production rollout.

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

Dynanet Team Requirements and Expectations:
  • Possess Strong written and verbal communication skills.
  • Highly organized with an ability to prioritize, balance, and effectively advance multiple competing priorities in a high-volume, fast-paced environment.
  • Ability to interact in a professional and collaborative manner with fellow Dynanet Teammates and the clients, and business partners that we work with.
  • Ability and desire to challenge and educate yourself to support and advance IT services delivery in the Federal agencies we serve.
  • Excellent judgment and creative problem-solving skills.
  • Respond to team member and client requests via email, MS teams, or other communication means during core business hours.
  • Active listening skills to understand clients' needs, and collaboration skills to work with other developers and designers.

Education/Experience Requirements:
  • Bachelor's degree in Data Science, Analytics, Computer Science, or related field
  • 4+ years of experience in data analysis, business intelligence, or analytics strategy
  • Demonstrated experience in analytics, BI, or data modeling
  • Experience working with federal agencies and understanding federal IT policies

Employee Benefits Overview:
  • Industry Competitive Compensation
  • Medical and Dental Insurance
  • Paid Time Off/Holidays
  • 401(k) Retirement Plans with Matching
  • Remote Work*
  • Paid Training
  • Employee Referral Program
  • Employee Development Program

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