Data Engineer
United Kingdom
Posted on 1/2/2024
INACTIVE
KoBold Metals

51-200 employees

Utilizes big data and AI for efficient mineral exploration
Company Overview
KoBold Metals is transforming the mineral exploration industry by leveraging statistical modeling, big data, and foundational ore-deposit science to enhance the discovery of natural resources essential for electric vehicles. Their unique approach, termed the Epistemology of Exploration, focuses on quantifying and reducing uncertainty in data, making the exploration process more efficient and scientific. Additionally, they've developed TerraShed, a proprietary data system that organizes, standardizes, and quality tests diverse geophysical data, providing a robust information repository for their scientists to drive further discoveries.
AI & Machine Learning
Data & Analytics
Energy
B2B

Company Stage

Series B

Total Funding

$410.3M

Founded

2018

Headquarters

Berkeley, California

Growth & Insights
Headcount

6 month growth

25%

1 year growth

88%

2 year growth

219%
Locations
Remote
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Python
Pandas
Data Analysis
CategoriesNew
Data Engineering
Data Management
Data & Analytics
Requirements
  • At least 5 years of experience in a Data Engineering or Software Engineering role
  • Proficiency in large-scale system design
  • Proficiency in Python, including data processing libraries such as pandas and distributed computing frameworks such as Dask
  • Proficiency in performance optimization for data storage and serving
  • Discerning ability, curiosity and initiative to identify inefficiencies and opportunities for automation. Creativity and follow-through to address these problems in a systematic way
  • Track record of scaling a fast-growing product, in a startup or as a member of a small team
  • Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations)
Responsibilities
  • Collect, standardize, clean, and organize heterogeneous mineral exploration data
  • Build tooling to support field operations such as dashboards, visualizations, data processing pipelines, integrations with third party software
  • Build scalable, reliable, and performant systems to support the above operations
  • Eliminate work through automation and efficiency improvements
  • Optimize existing systems and processes to increase scale and velocity of our data processing
  • Evangelize automation and engineering best practices throughout Kobold
  • Mentor other team members to adopt them
  • Work with data scientists and geoscientists to generate data that meet their data quality and accessibility requirements