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Analytics Engineer

Making electric vehicle charging smart and simple by building a giant, virtual charging platform with over 900,000 connected EV chargers globally.
Data
Mid-Level Software Engineer
Hybrid
1,000 - 5,000 Employees
3+ years of experience
Automotive · Enterprise SaaS

Job Description

Octopus Electroverse, a rapidly growing division of Octopus Energy Group, is seeking an Analytics Engineer to join their mission of revolutionizing electric vehicle charging. As part of a team managing over 900,000 connected EV chargers globally, you'll work on building and maintaining critical data infrastructure that powers their expanding international operations. The role offers end-to-end ownership of data pipelines, working with diverse datasets including charge point telemetry, user behavior, and operational metrics.

You'll be instrumental in building the data function, establishing best practices, and creating automated pipelines using modern tools like dbt, Databricks, Python, and AWS. The position requires a blend of technical expertise in data modeling, pipeline development, and analytics, along with the ability to collaborate across product, technology, and strategy teams.

The ideal candidate will bring strong experience in data modeling, dashboard development, and working with large-scale production datasets. You'll be working in a hybrid environment, with 1-2 days per week in the London office, as part of an award-winning company culture that was recognized as the best company to work for in 2022.

This role offers the unique opportunity to directly impact the transition to sustainable transportation while working with cutting-edge technology. You'll be part of a multifunctional team focused on making Octopus the go-to name in EV charging, with exposure to web, iOS, Android, CarPlay, and Android Auto platforms. The position combines technical challenges with meaningful work in sustainability, offering both professional growth and the chance to contribute to environmental impact.

Last updated 4 days ago

Responsibilities For Analytics Engineer

  • Develop and maintain data pipelines and automated processes in Airflow and Python
  • Create SQL data models with dbt to power dashboards and applications
  • Integrate third-party APIs and databases into data flows
  • Perform in-depth analysis and data transformations with SQL, Python, and Jupyter Notebooks
  • Prototype internal data applications and tools
  • Ensure data quality and reliability throughout the lifecycle
  • Collaborate with product, technology, and strategy teams to deliver insights and tools

Requirements For Analytics Engineer

Python
Kubernetes
  • Data Modelling Experience with dbt
  • Experience in creating data dashboards and developing data products
  • Experience working on collaborative projects with business teams
  • Ability to work independently and deliver pragmatic solutions
  • Proficiency in SQL, Python, pandas/numpy, Databricks/Jupyter Notebooks
  • Experience with large datasets in production environments
  • Strong time management skills
  • Passion for Net Zero and sustainability

Benefits For Analytics Engineer

  • Flexible work environment
  • Hybrid working model
  • Award-winning company culture
  • Named best company to work for in 2022
  • Top 50 best places to work on Glassdoor 2022

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