San Francisco, CA /
Growing Energy Labs, Inc (Geli) – Technology - Software Development /
This is a San Francisco based position that is currently remote and will have a hybrid schedule once we return to office. We are open to candidates willing to relocate to the San Francisco Bay Area.
Geli (Growing Energy Labs, Inc.) provides software and business solutions to design, connect, and operate energy storage systems ranging in size from residential to utility-scale, as well as grid-tied, microgrid, and off-grid systems. Geli’s suite of products creates an ecosystem where project developers, OEMs, financiers, and project operators can deploy advanced energy projects using a seamless hardware-agnostic software platform.
Geli is a subsidiary of Hanwha Q CELLS, one of the world’s largest photovoltaic manufacturers most recognized for its high-performance, high-quality solar cells and modules.
Geli is committed to helping make the planet a cleaner, better place to live, both with our software products and through our everyday actions.
Imagine a world where there is less reliance on non-renewable power, where you source your electricity from your neighbors rather than from power stations hundreds of miles away and software makes the best possible use of the solar, wind, and battery storage available. This is our vision.
We are looking for enthusiastic colleagues that are not only fluent in technology, but also share our vision of a world running on 100% renewable energy.
Geli is looking for an enthusiastic Data Engineer, who is eager to work at the forefront of the rapidly expanding energy storage industry. As part of our Data Science team, you will develop data workflows to support both our production systems and design tools. Data is at the core of all Geli’s products, so this position will give you plenty of opportunities to contribute to our platform.
- Build and maintain robust data pipelines.
- Collaborate with data scientists to understand data requirements of the machine learning and optimization models.
- Collaborate with software engineers and DevOps to develop appropriate technical solutions.
- Design and implement best practice approaches to data infrastructure, management and governance.
Required Experience and Skills
- A solid foundation in computer science and software engineering principles, including object-oriented programming.
- At least 2+ years of work experience as Data Engineer
- Experience writing clean, maintainable, efficient and thoroughly tested python (3.6+) code.
- Experience developing data pipelines and implementing data engineering best practices.
- Ability to work collaboratively with all levels and teams at Geli.
- Self-sufficient and proactive approach.
- Willingness to learn and adapt in the rapidly growing energy industry.
Desired Experience and Skills
- Knowledge of energy storage applications and renewable energy
- Familiarity with machine learning and optimization algorithms and concepts
- Docker, Kubernetes, AWS
- RabbitMQ, AMQP, Kafka
- Data Lakes and Data Warehouses
- PostgreSQL, Django ORM, Cassandra, Timescale DB, Redis, S3
BENEFITS OF WORKING AT GELI
Competitive salary commensurate with experience
Competitive benefits offerings
Convenient accessible location in downtown San Francisco
Flexible work-from-home-office opportunities, as determined by position and job duties
Make a difference: join a group of people who are passionate about renewable energy
Have an impact: the company is still small enough that everyone’s contribution has a significant impact to the success of the company
Many opportunities to lead teams, projects, and contribute to development
Casual professional working environment: there’s no need to dress up, just present your best self
Work collaboratively in a diverse environment- we commit to reaching better decisions by respecting opinions and working through disagreements
We value the insights that a diverse team can bring. We encourage applications from members of groups that have been traditionally underrepresented in tech.
Growing Energy Labs, Inc. provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, or genetics.