Staff Data Engineer

codeforamerica; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

Fully remote in US

40-hour work week, Mon–Fri

Professional-development funding

Health coverage options

Employer matching retirement

Job summary

Code for America is seeking a staff-level data engineer to lead the technical delivery of data infrastructure that underpins public-service products. You will combine hands-on engineering with architectural leadership, mentoring, and a focus on privacy, security, and responsible data use.

Responsibilities include designing scalable data pipelines in cloud environments, translating cross-team requirements into actionable plans, and ensuring operational reliability and governance across the data

Qualifications

• Experience leading the technical execution of data infrastructure projects and architectural decisions.
• Strong background building and operating production data pipelines and systems for analytics or reporting.
• Ability to collaborate with data scientists, software engineers, product managers, and DevOps partners.
• Experience diagnosing complex data problems balancing delivery with reliability, security, and governance.
• Excellent written and verbal communication documenting systems and decisions.

Responsibilities

• Design and deliver scalable data pipelines, transfers, transformations, integrations, and validation processes in cloud environments.
• Translate requirements from data science, software engineering, and product teams into practical data architecture and implementation plans.
• Improve consistency, performance, monitoring, deployment, and operational reliability of data systems.
• Investigate and resolve data-quality or infrastructure issues and recommend process improvements.
• Establish and promote practices for data governance, privacy, security, dataset management, and lifecycle controls.
• Provide technical direction and mentorship for data scientists and engineers.

Skills

Data infrastructure leadership

Production data pipelines

Cross-functional collaboration

Data governance

Clear communication

Job description

Role overview

Lead the technical delivery of data infrastructure that supports public-service products and the analysis used to evaluate their outcomes. This staff-level role combines hands‑on data engineering with architectural leadership, cross‑functional planning, mentorship, and a strong focus on reliability, privacy, security, and responsible data use.

Responsibilities

• Design and deliver scalable data pipelines, transfers, transformations, integrations, and validation processes in cloud environments.


• Translate requirements from data science, software engineering, and product teams into practical data architecture and implementation plans.


• Improve the consistency, performance, monitoring, deployment, and operational reliability of data systems.


• Investigate and resolve data-quality or infrastructure issues, communicate findings clearly, and recommend process improvements.


• Establish and promote practices for data governance, privacy, security, dataset management, documentation, and lifecycle controls.


• Provide technical direction, mentorship, written guidance, and enablement for data scientists and engineers.

Requirements

• Demonstrated experience leading the technical execution of data infrastructure projects and making sound architectural decisions.


• Strong background building and operating production data pipelines and systems that support analytics or reporting.


• Ability to collaborate effectively with data scientists, software engineers, product managers, and DevOps partners.


• Experience diagnosing complex data problems and balancing delivery needs with reliability, performance, security, and governance.


• Clear written and verbal communication skills, including the ability to document systems and explain technical decisions.

Benefits and work setup

• Fully remote work for employees residing in the United States, with a standard Monday–Friday, 40‑hour schedule.


• Internal collaboration hours are generally planned between 10 a.m. and 3 p.m. Pacific Time.


• Travel is expected to be no more than 10%.


• Professional-development funding, health coverage options, retirement contributions with employer matching, paid holidays, open personal time off, paid sick time, and paid parental and family leave are provided.