Similar Jobs
Equilibrium Energy is a team of technologists, power market experts, and AI pioneers reimagining how the world’s most critical industry operates. We’re building a first-of-its-kind AI operating system for the power sector, uniting cutting-edge science with real-world purpose to enable a cleaner, more resilient energy future. At EQ, you’ll join a tight-knit group of brilliant, curious, and adventurous people who bring the same energy to collaboration as they do to innovation.
Equilibrium Energy is a well-funded, Series B clean energy startup backed by some of the most prominent institutional investors in climate. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We’re looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.
What we are looking for
Data is central to the success of the Equilibrium Energy mission. The data managed by the Data Services team is incredibly robust ranging from telemetry outputs to inputs into machine learning models and includes public, proprietary and private data points. All of this needs to be centralized, synthesized and governed to ensure its secure usability across our various teams. The role of the Energy Analyst is to advance our data system and platform so it will empower our teams to better utilize our market data warehouse. The Energy Data Strategist will do this by applying domain and market expertise to advance our raw data into explorable, understandable data views and processes. The ideal candidate will have a passion for energy markets, data engineering and analytics.
What you will do
Engineering and Analytics
- Work closely with data engineers to define data ingestion requirements
- Define, refine and apply our standard data model
- Capture data utilization requirements from end-users
- Develop end-user tables within Databricks utilizing SQL and DBT
- Seek out and collect feedback to improve our data life-cycle
- Create information that supports our semantic layer and data ontology
Data Support and Quality Assurance
- Define and manage quality assurance processes in our data layers
- Research market data, review technology forums and monitor market publications to ensure we are future proof to new products and changes in reporting requirements
The minimum qualifications you’ll need
- Passion for clean energy and fighting climate change
- BS/Master's degree in a quantitative discipline (e.g., Computer Science, Operations Research, Industrial Engineering, Mathematics, Finance, Economics, Physics, Electrical Engineering) or equivalent practical experience.
- 7+ years experience with energy market data, including nodal power market results, forecasting, and market research.
- Demonstrated experience with SQL and Python; ability to translate raw data into clean market views that allows the business to analyze market data.
- Effective communication skills to synthesize business needs to translate into product requirements.
Nice to have additional skills
- Demonstrated experience in DBT and Databricks
- Deep expertise with Business intelligence tools, including Sigma, Hex, PowerBI, or Tableau.
- Experience communicating the results of analyses with product, engineering, and leadership teams to influence product and engineering strategy.
- Demonstrated proactivity and self-direction. Willingness to teach as well as learn.
- Excellent team collaboration skills and collaboration-first mentality.
- Experience with trading systems.
We are a high growth company with accelerating hiring needs so there’s a great chance we’ll be able to create a custom role for you, now or in the future. All roles, titles and compensation packages are tailored to the applicant, so apply anyways and tell us in your cover letter about your dream role.
What we offerEquilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software & ML engineering. Our experience in the space means we’ve previously built versions of nearly every technical component of our platform. We are now designing them better, and combining them in a holistic and novel way, to achieve global scale and climate impact. We pride ourselves on our deeply empathetic & collaborative culture, honest and direct but respectful communication, and our balanced, flexible, and remote-first work environment.
Employee benefits include:
- Competitive base salary and a comprehensive medical, dental, vision, and 401k package
- Opportunity to own a significant piece of the company via a meaningful equity grant
- Unlimited vacation and flexible work schedule
- Accelerated professional growth and development opportunities through direct collaboration and mentorship from leading industry expert colleagues across energy and tech
Equilibrium Energy is a diverse and inclusive, equal opportunity employer that does not discriminate on the basis of race, gender, nationality, sexual orientation, veteran status, disability, age, or other legally protected status.
Equilibrium Energy San Francisco, California, USA Office
San Francisco, CA, United States
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
