Life at Plume At Plume, we believe that technology isn't about moving faster, it's about making life’s moments better. Which is why we’ve built the world's first, and only, open and hardware-independent service delivery platform for smart homes, small businesses, enterprises, and beyond. Our SaaS platform uses WiFi, advanced AI, and machine learning to create the future of connected spaces—and human experiences—at massive scale.

We now deliver services to over 60 million locations globally and have managed over 3 billion devices on our platform. We’re expanding rapidly, pioneering a new category, and we achieved our Series F funding in just four years. Our customers include many of the world's largest Internet Service Providers (ISPs) who look to Plume to help them evolve their smart home offerings while gleaning insights from their own data.

With a bias for action and a love for being trailblazers, the team at Plume embodies a combination of relentless curiosity and imaginative innovation. We challenge ourselves to think in ways that other companies don't, work to do what should be done (rather than what can), and if we can’t do it exceptionally well, we don’t do it. It’s how we've assembled a team of world-class builders, thinkers, and doers.

And it’s how we’re reinventing what’s possible every day. Role Description: Plume’s Data Services team is looking for engineers to build and operate data pipelines that power the gamut of Plume products and analytics.

Requirements

of many of our use cases, you will be solving challenging problems on a daily basis using a variety of cutting-edge technologies.

and translate them into robust pipeline designs Build and maintain high-quality data pipelines with strong reliability and data integrity standards Own data warehouse schema documentation and keep it current as systems evolve Write clean, well-structured code and contribute to a culture of rigorous peer review Continuously refactor and optimize pipelines for performance, cost efficiency, and operational simplicity Triage and resolve production issues related to data quality and availability Mentor junior engineers and new hires, helping them ramp up quickly and contribute confidently Uphold data governance

including access controls, retention policies, residency rules, and de-identification Contribute to the technology roadmap and drive best practice adoption across the team Orchestrate complex workflows in Apache Airflow writing DAGs, managing dependencies, and building in automated error handling Implement granular access controls and data security policies using AWS Lake Formation Integrate automated data quality checks into deployment pipelines so issues are caught before they reach production

Responsibilities

: Partner with stakeholders to define data

Qualifications

: 5+ years of software development experience building, scaling, and supporting production data pipelines Hands-on expertise with AWS big data services particularly Athena for distributed querying and Lake Formation for security, cataloging, and access management Solid Apache Airflow experience: writing DAGs, managing task dependencies, and debugging runtime failures A DataOps mindset comfortable with CI/CD for pipelines, environment monitoring, IAM/permissions management, and owning what you ship Strong Python skills for scripting, automation, and Airflow orchestration; proficiency in Java or Scala for core pipeline development High proficiency in SQL across data warehousing technologies Deep understanding of large-scale data processing frameworks, preferably Apache Spark (Flink experience a plus) Solid grasp of data warehousing concepts and design patterns Strong analytical thinking and clear, effective communication written and verbal Please note that visa sponsorship is not available for this role.

Compensation

package would include an anticipated

range of $149,000.00 - $194,

Staff Software Engineer (Data Engineer)