DevOps Engineer, Data

About Good Leap:

Good Leap is a technology company delivering best-in-class financing and software products for sustainable solutions, from solar panels and batteries to energy-efficient HVAC, heat pumps, roofing, windows, and more. Over 1 million homeowners have benefited from our simple, fast, and frictionless technology that makes the adoption of these products more affordable, accessible, and easier to understand. Thousands of professionals deploying home efficiency and solar solutions rely on Good Leap’s proprietary, AI-powered applications and developer tools to drive more transparent customer communication, deeper business intelligence, and streamlined payment and operations.

Our platform has led to more than $30 billion in financing for sustainable solutions since 2018.

Good Leap is also proud to support our award-winning nonprofit, Give Power, which is building and deploying life-saving water and clean electricity systems, changing the lives of more than 1.6 million people across Africa, Asia, and South America.

The Staff Data Ops Engineer role applies Dev Ops principles to data platforms, ensuring that pipelines and systems are automated, observable, and reliable  this role, the engineer partners closely with data engineering, analytics, and infrastructure teams to enable consistent, secure, and performant delivery of data. The Staff Data Ops Engineer is a leader who sets strategy for Data Ops, designs platform-wide automation and observability patterns, and unblocks teams on their hardest data reliability challenges.

• Define and drive adoption of CI/CD frameworks, infrastructure-as-code, and automation patterns for data platforms. Strong communication, influence, and empathy are critical.
• Lead multi-quarter initiatives that materially improve the reliability, scalability, or cost efficiency of data systems. Requires composure under pressure, clear decision-making, and the ability to unite cross-functional teams.
• Establish and maintain data observability standards (freshness, accuracy, completeness, lineage). Partner with product and data teams to define and track SLIs/SLOs for critical pipelines.
• Mentor senior and mid-level Dev Ops and Data Engineers, fostering a culture of automation, reliability, and continual learning.
• Represent Data Ops in executive and stakeholder reviews, translating data reliability risks into business impact to support prioritization and decision-making. Strong written communication and clarity are essential.

• Set Data Ops strategy:Define and evangelize CI/CD, observability, and testing frameworks adopted by a majority of data services and pipelines.
• Architect at scale:Design resilient, cost-efficient data platform architectures across cloud and on-prem environments (batch and streaming).
• Standardize the platform:Author Terraform modules, orchestration templates (Airflow/dbt/Dagster), and hardened container images for data workloads.
• Advance observability:Lead adoption of data monitoring and lineage tools that cut data incidents and MTTR by double digits.
• Drive incident excellence:Act as incident commander for major data outages, run blameless postmortems, and eliminate systemic pipeline toil.
• Mentor & influence:Coach senior engineers, run Data Ops workshops, and contribute to role definition and career-ladder standards.
• Cross-team collaboration:Partner with Security, Compliance, and Operations to balance reliability, cost, and speed in the same manner that new product features are considered.
• Infrastructure and Deployment:Strong hands on experience with infrastructure as code (IaC) such as Terraform and automated deployments such as Git Hub Actions.

$173,000 - $200,000 a year

In addition to the above salary, this role may be eligible for a bonus.

Job duties include additional responsibilities as assigned by one's supervisor or other managers related to the position/department. This job description is meant to describe the general nature and level of work being performed; it is not intended to be construed as an…