Senior Software Engineer (Data Platform)

Amplify Renewables is a systematic energy forecasting and trading company improving the predictability and reliability of the grid. We process large amounts of multifaceted data (market, generator, weather, outage, etc.) and build models that will forecast the grid. We are a technology-first company with significant machine learning and quantitative trading experience at top US funds. We are profitable and growing quickly.

We are hiring a senior software engineer to help build and maintain our data platforms for both production and research. These are systems that download data for our production processes and for our research datasets. The ideal candidate is process-focused and able to lead technical direction for all of the company's data systems. The ability to clearly communicate about technical concepts and plans in written form is a requirement for this job.

Key responsibilities:

• data ingestion: plan and execute systematic projects to improve the production infrastructure we use to ingest, clean, and standardize schemas and contracts for data from widely varying data providers. Solve production issues related to the data platform and provide root cause analyses for incremental improvements to reliability.
• research infrastructure: scale our custom research infrastructure to multi-node + multi-cores paradigms. Increase the robustness and capabilities of our core research code and methods.

For example, a first major project once hired and onboarded would be to make a plan for migrating our data and methods from single market focused to market-agnostic (i.e. like a single tenant to multitenant architecture). This role would be one of the first technical hires and report directly to a partner, who they would work closely with for several months (however, most work interfaces with everyone at the team).

Required skills & experience:

• 4+ years of experience developing and maintaining software
• Fluency with Python, including packaging and testing Experience with distributed computation or high performance computation
• Comfortable with high level and lower level systems thinking Able to communicate effectively in written and spoken English (short and long form)
• Able to fill knowledge gaps quickly by learning technical concepts rapidly and precisely Ideal skills & experience
• Experience working on small, fast-moving teams
• Experience with "data lake" architectures (e.g. Parquet-based)
• Comfortable programming in Rust, especially optimizing Python code with Rust extensions
• Columnar database management experience, such as Clickhouse or Snowflake
• LLM-assisted development ("agents") to speed up implementation of tightly scoped projects

What success looks like (for example):

• Within 30-60 days you can independently ship meaningful improvements to the data platform after aligning with the team.
• Within 90 days the core data ingestion infrastructure has well-defined contracts and is testable.
• Within 180 days we have moved to a market-agnostic framework and are able to rapidly onboard new markets.

Our AI coding policy:

A human employee is ultimately responsible for the work product, including testing, reviewing, and communicating about outcomes, whether the code is written by a human or an LLM. The ideal candidate is rigorous and skeptical about LLM output and understands this responsibility, but ready to learn more as the space changes rapidly. See here for more details about an AI assistance policy that matches our own.

Remote work:

This position is remote-first, with the possibility of in-person work if the candidate is located in or willing to relocate to San Francisco or Seattle. We expect to meet in person regularly around once a quarter. For non-US candidates, we expect candidates to be comfortable working hours that overlap for at least 4 hours with PST, and to spend some of those hours on a video call working together. We are a deep work focused company, and as a result expect candidates to be proactive about regularly communicating in written form (emails, Slack messages, etc.).