Data Engineer

Summary

NAMI is a national organization supporting individuals and families affected by mental illness through programs and services. The Data Engineer will build and operate NAMI's data platform, including ELT pipelines, data warehouse infrastructure, transformations, reporting, quality testing, monitoring, and CI/CD, while partnering with stakeholders and establishing data engineering standards.

Responsibilities

• Help leadership measure program impact and make well-informed strategy decisions by building NAMI's central data warehouse and ELT pipeline from sources across the organization (e.g., micro-services, Salesforce, and the LMS)
• Reduce manual reporting by giving state organizations, local affiliates, and colleagues richer, on-demand access to their data - partnering directly with stakeholders to stand up curated datasets and self-service reporting that replace today's hand-built affiliate reports
• Ensure every team can trust the data behind its decisions by expanding automated quality testing, monitoring, and CI/CD as the platform grows - and owning incidents end-to-end, source to dashboard, when something slips through
• Set the foundation every future data hire builds on - as the team's first dedicated data engineer, establish the standards, patterns, and review practices that define how NAMI does data

Skills

• 3-5 years in data, analytics, or backend engineering
• Proficiency in SQL and Python
• Experience with version-controlled production ELT/ETL pipelines, including testing and monitoring
• Solid grasp of data modeling (e.g., dimensional modeling, layered architecture)
• Experience with a modern cloud data warehouse
• Communicates technical concepts clearly to non-technical colleagues
• Employees must be available during standard business hours, with core hours between 10:00 a.m. - 3:00 p.m. ET
• 10 - 20%.travel, including overnight
• Prolonged periods of sitting at a desk and working on a computer
• * 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

Qualifications

Must Haves

• 3-5 years in data, analytics, or backend engineering
• Proficiency in SQL and Python
• Experience with version-controlled production ELT/ETL pipelines, including testing and monitoring
• Solid grasp of data modeling (e.g., dimensional modeling, layered architecture)
• Experience with a modern cloud data warehouse
• Communicates technical concepts clearly to non-technical colleagues
• Employees must be available during standard business hours, with core hours between 10:00 a.m. - 3:00 p.m. ET
• 10 - 20%.travel, including overnight
• Prolonged periods of sitting at a desk and working on a computer

Nice to Haves

• * 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

Benefits

• A collaborative team
• Flexible remote environment
• Knowledge sharing, professional development, and continuous improvement
• 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
• A variety of wellness offerings to support team members
• Employee Referral Program
• The Employee Assistance Program (EAP) which provides support for personal and family problems common in contemporary life