Application Guide

How to Apply for Senior Analytics Engineer

at Form Energy

🏢 About Form Energy

Form Energy is pioneering affordable, long-duration energy storage solutions critical for achieving a 100% renewable electric grid. Unlike typical tech companies, they're tackling one of the most pressing climate challenges by developing multi-day battery storage systems that can power grids when renewable sources aren't available. Working here means directly contributing to decarbonization with technology that could transform global energy infrastructure.

About This Role

As a Senior Analytics Engineer at Form Energy, you'll build and optimize the data models that measure product performance and operational efficiency of their innovative battery systems. You'll translate complex engineering and operational data into actionable insights using tools like dbt, Spark, and Delta Live Tables, directly influencing how the company scales its technology. This role sits at the intersection of data engineering and product analytics, ensuring data consistency across software systems while enabling data-driven decisions about battery performance and reliability.

💡 A Day in the Life

You might start by reviewing dbt model runs from overnight battery performance data, then meet with battery engineering teams to refine key degradation metrics. Afternoon could involve optimizing Spark jobs processing terabyte-scale telemetry data, followed by building new Grafana dashboards for operations teams to monitor system health. You'll regularly collaborate with software engineers to ensure new data sources integrate cleanly with existing models.

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Interview Prep

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🎯 Who Form Energy Is Looking For

  • Has 7+ years specifically building production data pipelines and models for physical products or IoT systems (not just web analytics), with proven experience in dbt and Apache Spark for large-scale time-series data
  • Demonstrates deep expertise with OLAP databases (Snowflake/Databricks) AND time-series databases (InfluxDB/Clickhouse) for handling sensor/telemetry data from energy storage systems
  • Can bridge technical data work with cross-functional collaboration, having experience defining key metrics with engineering teams and managing analytical tool integrations (Grafana, Sigma, Hex)
  • Shows understanding of energy systems, grid operations, or hardware product analytics, with Python/SQL skills applied to performance monitoring and reliability analysis

📝 Tips for Applying to Form Energy

1

Highlight specific experience with time-series data from physical systems (sensors, IoT, industrial equipment) rather than just web/app analytics

2

Quantify your impact with metrics related to data model optimization, query performance improvements, or reliability monitoring in previous roles

3

Mention any experience with energy, grid, battery, or hardware data specifically - even if tangential

4

Demonstrate how you've worked with engineering teams to define product performance metrics, not just reported on existing ones

5

Show familiarity with their tech stack by mentioning specific experience with dbt + Spark + Grafana/Sigma combinations in production environments

✉️ What to Emphasize in Your Cover Letter

['Your experience with time-series data and performance metrics for physical products or industrial systems', 'Specific examples of building data models that influenced product decisions or operational improvements', "How you've managed data consistency across multiple sources and systems in complex environments", "Why long-duration energy storage and Form Energy's mission specifically motivates you (reference their technology)"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Form Energy's iron-air battery technology and how it enables 100+ hour storage (watch their technical presentations)
  • → The challenges of grid-scale energy storage and why long-duration storage matters for renewable integration
  • → Their partnerships with utilities like Xcel Energy and Georgia Power to understand real-world deployment contexts
  • → Recent news about their manufacturing scale-up and Series E funding to understand growth trajectory

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 How would you design data models to track battery performance metrics over multi-day cycles?
2 Describe your experience optimizing dbt models or Spark jobs for large-scale time-series data
3 How do you ensure data quality and consistency when working with engineering teams upstream?
4 What approaches have you used to define and calculate key performance indicators for hardware products?
5 How would you set up monitoring/alerting for battery system anomalies using Grafana and their data platform?
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⚠️ Common Mistakes to Avoid

  • Focusing only on web/marketing analytics experience without demonstrating hardware/IoT/time-series data work
  • Generic statements about 'passion for sustainability' without showing understanding of their specific technology
  • Listing dbt/Spark as buzzwords without concrete examples of building production data models with them

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to Form Energy!

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