How to apply for Staff Engineer, Data (Remote, US)

About Renew Home

Everyday Electric (formerly Renew Home) is building the largest residential virtual power plant in North America. It partners with industry-leading brands to manage residential energy for efficiency, savings, and comfort. The company is an Equal Opportunity employer focused on a diverse, equitable, and inclusive work environment.

About the role

This is a staff data engineer role focused on end-to-end data platform strategy, real-time streaming pipelines, and an enterprise data lakehouse. You will architect high-throughput, fault-tolerant infrastructure that processes streaming device telemetry from millions of connected homes. The role is a high-impact individual contributor position with technical leadership responsibility, including mentoring engineers across the organization.

A typical day

A typical day likely involves designing or reviewing streaming pipeline architecture, working with engineers on data platform problems, and making decisions about the lakehouse ecosystem. You may also mentor engineers and coordinate with teams that depend on telemetry data. The exact routine is not listed, so ask about team structure and daily collaboration during interviews.

Who Renew Home is looking for

• Has experience architecting high-throughput, fault-tolerant data platforms and real-time streaming pipelines at scale.
• Has built or maintained enterprise data lakehouse ecosystems that support analytics, operational insights, and machine learning.
• Has processed streaming device telemetry or similar high-volume event data from large numbers of connected sources.
• Is comfortable as a senior individual contributor who mentors other engineers and acts as a force multiplier across an engineering organization.

Tips for this application

• Highlight any experience processing streaming telemetry from connected devices, IoT, or large-scale event sources, since the role centers on millions of connected homes.
• Use concrete numbers when describing past data platforms: throughput, number of devices or events, latency, uptime, and data volume.
• Name the specific streaming and lakehouse technologies you have used, and describe the architecture decisions you made and why.
• Show evidence of technical leadership as an individual contributor, such as mentoring engineers, setting platform direction, or leading cross-team design reviews.
• Check the company website at www.everydayelectric.com before applying and reference the residential virtual power plant model in your materials.

What to cover in your cover letter

['Your experience designing high-throughput, fault-tolerant streaming pipelines and the scale you handled.', 'How you have built or shaped a data lakehouse ecosystem that serves analytics, operations, and machine learning.', 'Your track record as a senior individual contributor who mentors engineers and multiplies team output.', 'Why residential energy management and the virtual power plant model interest you specifically.']

Research before applying

• Read the company website at www.everydayelectric.com to understand the residential virtual power plant model and the rebrand from Renew Home.
• Look into what a virtual power plant is and how residential energy devices are coordinated on the grid.
• Find the industry-leading brands the company partners with and how those partnerships affect data flows.
• Check for any public engineering content or job posts that describe the current data stack and team structure.

Likely interview topics

Based on the job description, expect questions about:

• How you would architect a real-time streaming pipeline for telemetry from millions of connected homes.
• Trade-offs between different lakehouse designs for analytics, operational insights, and machine learning workloads.
• How you ensure fault tolerance and high throughput in a data platform under heavy load.
• Examples of mentoring engineers or driving technical direction as a staff-level individual contributor.
• How you would handle schema evolution and data quality for streaming device telemetry.

Common mistakes to avoid

• Submitting a generic data engineering resume with no mention of streaming telemetry, real-time pipelines, or lakehouse work.
• Claiming staff-level leadership without concrete examples of mentoring, platform strategy, or cross-team influence.
• Ignoring the energy domain and the virtual power plant context, which is central to the role and company.