Sr. Analytics Engineer

Who We Are 

Arcadia is the technology company empowering energy innovators and consumers to fight the climate crisis. Our software and APIs are revolutionizing an industry held back by outdated systems and institutions by creating unprecedented access to the data and clean energy needed to make a decarbonized energy grid possible.

In 2014, Arcadia set out on its mission to break the fossil fuel monopoly and since then we have been knocking down the institutional barriers to unlock decarbonization.  To date, we have connected hundreds of thousands of consumers and small businesses with high-quality clean energy options. Fast forward to today, and now, we’re thinking even bigger.  We have launched Arc, an industry-defining SaaS platform that empowers developers and energy innovators to deliver their own custom, personalized energy experiences, accelerating the transformation of the industry from an analog energy system into a digitized information network.

Tackling one of the world’s biggest challenges requires out-of-the-box thinking & diverse perspectives. We’re building a team of individuals from different backgrounds, industries, & educational experiences. If you share our passion for ushering in the era of the clean electron, we look forward to learning what you would uniquely bring to Arcadia!

We are seeking a Senior Analytics Engineer to join the Data team. This individual will collaborate with the Director of Analytics Engineering and contribute to Arcadia’s Lakehouse, starting from the raw data in the data lake to build powerful and sophisticated business concepts that can be demonstrated to drive analytics, insights and data products and automations. The ideal candidate is a data owner who loves building business concepts and structures out of complex, unstructured data sets.

Arcadia is a data company, and Analytics Engineering is an integral part of our goal to describe and grow the business. The successful candidate will be a key contributor to the Data team, enabling analytics, automation, and data product development with innovative, industry-leading analytics engineering solutions.

Arcadia is headquartered in Washington, DC, and open to fully remote candidates.

• Partner with the Analytics team to deeply understand business and product requirements
• Build and maintain the Lakehouse architecture; that could include metrics framework, business automation workflows, product base tables, etc.
• Contribute scaling and maintaining a complex data stack based on market-leading technology (Showflake, dbt, Hex, Lightdash)
• Serve as a critical analytics engineering SME for the Data team
• Drive a culture of urgency, impact, intellectual curiosity and continuous improvement

• At least 6 years of experience in data roles, at least 4 of which as a developer in analytics engineering, data engineering or technical analytics
• Proficiency in Python and SQL
• Proficiency in engineering best practices (sprints, code reviews, etc.)
• Outstanding sense of ownership and ability to partner with Data Engineering and with Analytics to build the best data solutions for Arcadia
• Strong communication skills and ability to partner cross-functionally to deeply understand requirements

• Experience with CI/CD development
• Experience with venture-backed start-ups
• Experience working in global, distributed teams

Benefits:

• "Remote first" culture - work anywhere in the US as long as you have a reliable internet connection
• Flexible PTO - no accrued hours and no limit on the number of vacation days employees can take each year
• 17 annual company-wide holidays including a week long "summer break"
• 10 days sick leave
• Up to 4 weeks bereavement leave
• 2 volunteer days off
• 2 professional development days off
• 12 weeks paid parental leave for all parents
• Weekly "flex time" - no internal meetings on Tuesdays and Friday afternoons
• 80-95% employer cost coverage for medical, dental, and vision benefits for employees and dependents
• A supportive engineering culture that values diversity, empathy, teamwork, trust, and efficiency