Staff Engineer, Data - Renew Home

Who We Are

Renew Home is on a mission to change how we power the world by making it easier for customers to save energy and money at home as part of the largest residential virtual power plant in North America. We partner with industry-leading brands to better manage residential energy for users by prioritizing efficiency, savings, and comfort — and cleaner energy for everyone.

We are an Equal Opportunity employer striving to create a diverse, equitable, and inclusive work environment where everyone feels that they have a voice that is heard.

Role Summary

At Renew Home, we are committed to transforming how residential energy is managed across North America. As a Staff Data Engineer, you will serve as a foundational technical leader shaping our end-to-end data platform strategy, real-time streaming pipelines, and enterprise data lakehouse ecosystem. You will architect high-throughput, fault-tolerant infrastructure capable of processing streaming device telemetry from millions of connected homes to support scalable analytics, operational insights, and machine learning initiatives.

This is a high-impact individual contributor role with meaningful technical leadership responsibility. You will act as a force multiplier across the engineering organization by mentoring engineers, incorporating feedback, influencing engineering culture, and helping shape how we work.

What You Will Do

• Define and drive the long-term data architecture vision, roadmap, and design standards across Renew Home's virtual power plant ecosystem, ensuring high availability, security, scalability, and resilience.
• Lead the design and implementation of fault-tolerant batch and real-time streaming data infrastructure capable of continuously processing data from millions of connected devices.
• Collaborate closely with application and analytics engineering teams to drive data architecture vision and delivery.
• Direct database architecture and continuous performance tuning across PostgreSQL Aurora, AWS Redshift, and query engines through advanced indexing, partitioning, and workload management strategies.
• Set high technical standards for data pipeline development, monitoring, data quality, and uptime; actively lead infrastructure management and support operations in our on-call rotation.
• Mentor and guide senior and mid-level data engineers, promoting engineering best practices, architectural design reviews, and technical growth across the organization.
• Continuously evaluate, prototype, and integrate modern data technologies and frameworks (e.g., Python, Redshift, Postgres, AWS/GCP, Lambda, Kinesis, Prefect, Iceberg, Terraform) to ensure optimal system evolution.

Requirements

• 10+ years of software and data engineering experience, with a proven track record of architectural leadership at scale.
• Bachelor's or Master's degree in Computer Science, Software Engineering, or equivalent practical experience.
• Proven experience designing, building, and operating production-grade high-volume batch and real-time data streaming architectures using technologies like GCP PubSub, AWS Kinesis, AWS Lambda, Apache Kafka and Apache Flink.
• Deep expertise in building scalable data lake architectures (AWS S3, Iceberg, AWS Glue, Delta Lake) and managing structured and unstructured device telemetry data.
• Expert hands-on proficiency in database design, performance tuning, query optimization, indexing, and partitioning with AWS Redshift and PostgreSQL Aurora.
• Mastery of Python and SQL with strong software engineering principles, CI/CD, and Infrastructure as Code using Terraform, CDKTF and AWS CDK.
• Self-starter with exceptional analytical and problem-solving skills, capable of turning complex ambiguous problems into clean, scalable technical solutions.
• Demonstrated ability to mentor engineering talent, drive cross-functional alignment, and champion data infrastructure best practices across multiple teams.
• Bonus Skills:
  • Extensive experience optimizing enterprise-scale data warehouses and leveraging advanced Redshift capabilities.
  • Hands-on experience with big data engines (e.g., Apache Spark, Ray) or building end-to-end Machine Learning pipelines.
  • Active contributions to open-source data ecosystems or relevant advanced certifications.

What You'll Get

• Competitive base salary of $170k - $220k with a target annual bonus of 15% and long-term incentive programs.
• Fully remote work environment with home office set-up allowance.
• Real and lived work-life balance with flexible PTO and parental leave benefits.
• Competitive health and wellness benefits package.
• 401(k) plan with employer contributions.
• Opportunity to work with an amazing mission-driven team.