Build and run NAMI’s data platform to enable program impact measurement and data-informed decisions across national, state, and local teams.

Design and implement a central data warehouse and ELT pipelines that pull from organizational sources such as micro-services, Salesforce, and the LMS
Enable leadership and teams to measure program impact by supporting strategy decisions with reliable, integrated data
Lower manual reporting by delivering curated datasets and self-service reporting for state organizations and local affiliates, replacing hand-built affiliate reports
Partner with stakeholders to expand on-demand access to data and support adoption of improved reporting workflows
Own data quality by expanding automated quality testing, monitoring, and CI/CD as the platform scales
Handle incidents end-to-end, from source to dashboard, when issues slip through automated checks
Establish the foundation for future data hires as the team’s first dedicated data engineer, setting standards, patterns, and review practices
Build and operate the end-to-end platform: ingestion, transformation, orchestration, and reporting
Build and operate ELT pipelines
Create well-modeled transformations using analytics engineering best practices
Develop trusted, well-documented data products and contribute to their continuous improvement within established architectural patterns

3-5 years in data, analytics, or backend engineering
Strong proficiency in SQL and Python
Experience with version-controlled production ELT/ETL pipelines, including testing and monitoring
Solid understanding of data modeling (e.g., dimensional modeling, layered architecture)
Experience with a modern cloud data warehouse
Ability to communicate technical concepts clearly to non-technical colleagues

Hands-on experience with a SQL transformation framework such as dbt
Exposure to managed ingestion or orchestration tooling (e.g., Fivetran, Airbyte, Dagster, Airflow)
Experience with a BI tool such as Power BI, Tableau, or Metabase
Experience helping evaluate, adopt, or migrate to new data tooling

Arlington, VA (hybrid; remote or optionally hybrid based on preference)
Availability during standard business hours with core hours between 10:00 a.m. and 3:00 p.m. ET
10-20% travel, including overnight

Generous and comprehensive Health, Dental, and Vision Plans
Paid Time Off: Vacation, Personal, and Sick Leave
Paid Parental Leave
403(b) retirement plan
Flexible Spending Accounts for health care, dependent care, and commuter expenses
Life Insurance and Disability coverage paid by NAMI
Flexible Work and Telework programs
Professional Development Reimbursement program
Wellness offerings to support team members
Employee Referral Program
Employee Assistance Program (EAP) for personal and family support

Data Engineer

Job Description