Staff Software Data Infrastructure Engineer
Peak EnergyBurlingame, CA$200k – $270kPosted 16 March 2026
Job Description
Job Title:
Staff Software Data Infrastructure Engineer
Location:
Burlingame, CA (Onsite)
Department:
ESS Engineering
Position Type:
Full-time
About the Company:
Peak Energy is the first American venture to advance globally proven Sodium-Ion battery systems as the storage standard for the new era of renewable energy on a resilient grid.
Sodium-Ion is cheap, readily available, and safe, making it the leading contender in a rapidly evolving market.
Our leadership team is powered by decades of expertise in scaling gigawatt-level innovation at world-class companies such as Tesla, Northvolt, SunPower, Fluence, and Enovix. We are backed by strategic investment and product partners such as TDK Ventures and Eclipse Ventures.
We are a team of engineers, operators, entrepreneurs, and partners driven by a shared ambition to set the new performance standard for renewable energy and grid resilience.
About the Job:
Peak Energy is looking for a
Staff Software Data Infrastructure Engineer
to own and scale the
battery data pipeline
that powers our engineering, test, and product development efforts. This role will be responsible for ensuring we capture
high-quality data from battery cells, modules, packs, and energy storage systems
, and turn that into reliable, accessible datasets for analysis, modeling, diagnostics, and decision-making.
This person will operate as a technical leader—bringing strong engineering fundamentals, a high ownership mindset, and a practical, execution-driven approach. You’ll partner closely with hardware, firmware, test, and systems teams to define what “good data” looks like and build robust infrastructure to deliver it.
Responsibilities:
Battery Data Pipeline Ownership
Design, build, and maintain end-to-end pipelines that ingest data from ESS platforms (cells → systems → full sites)
Own data flow from device-level sources through validation, storage, transformation, and delivery to downstream users
Improve reliability, scalability, and observability of the data pipeline as Peak scales development and testing
Data Quality, Validation, and Debugging
Define data quality standards and implement validation checks (schema enforcement, unit consistency, timestamp integrity, missing/duplicate values, etc.)
Build tools and processes to detect and prevent bad data from reaching engineering and analytics stakeholders
Support root-cause investigation for data gaps, telemetry issues, and sensor/firmware integration challenges
Storage, Access, and Infrastructure
Build and maintain storage and query systems designed to support an initial production-ready timeseries and structured battery telemetry pipeline
Partner with engineering stakeholders to enable fast, trustworthy access to critical datasets for testing, modeling, and product validation
Develop systems that support both real-time and offline workflows, depending on product and test requirements
Cross-Functional Collaboration
Work closely with firmware, electrical, test, systems engineering, and manufacturing teams to define data requirements and ensure instrumentation supports program goals
Translate real-world telemetry into usable engineering data products
Communicate status, tradeoffs, and recommendations to technical and non-technical partners
Engineering Leadership
Raise the bar for infrastructure design, code quality, and operational excellence
Mentor other engineers and contribute to technical direction for Peak’s broader data systems
Drive a culture of rapid iteration, clear ownership, and execution-focused engineering
Minimum Qualifications:
Bachelor’s degree in Computer Science, Electrical Engineering, Mechanical Engineering, or related field (or equivalent practical experience)
7+ years of software engineering experience, including ownership of production infrastructure and systems
Experience building and operating data pipelines and distributed systems in production environments
Strong fundamentals in debugging, syst ... (truncated, view full listing at source)
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