Octoenergy28d ago

Analytics Engineer

London (gb)Full-timemid

Data ScienceData EngineerAnalytics EngineerDataData & AI

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Overview

About Octopus Electroverse We’re making electric vehicle ownership as smart and as simple as possible by building the giant, virtual charging platform of the future. In just four years,

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Data ScienceData EngineerAnalytics EngineerDataData & AI

We’re making electric vehicle ownership as smart and as simple as possible by building the giant, virtual charging platform of the future.

In just four years, Octopus Electroverse has grown to become one of the largest eMobility players globally, with over 1 million connected electric vehicle chargers and a customer ecosystem spanning web, iOS, Android, CarPlay, Android Auto & Automotive OS, and more.

But it’s just the start: we’re busy expanding internationally, working with more automotive and tech partners, building exciting new features at scale, and creating the integrated charging experiences of the future - all in the name of making public EV charging super simple for customers.

Electroverse is a multifunctional team made up of product, development, commercial, operations, marketing, partnerships and more - all focused together on making Octopus the go-to name in EV charging.

We are seeking a passionate data professional to drive the electrification of transport by transforming complex information into strategic assets. You will work with a rich variety of datasets, including charge point telemetry, user behaviour, marketing campaigns, sales figures, and operational metrics. Your mission will be to present data with the aim of uncovering actionable insights that enhance efficiency and guide decision-making across the entire business.

This role offers end-to-end ownership of the data pipeline. As a key member of a small, high-growth team, you will do more than just manage data; you will be instrumental in building our data function. This includes establishing best practices, creating automated pipelines, and shaping the foundational framework for how we leverage data to succeed.

You'll create SQL data models with dbt to power dashboards and applications

You'll develop and maintain data pipelines and automated processes in Airflow and Python

You'll integrate third-party APIs and databases into our data flows

You'll perform in-depth analysis and data transformations with SQL, Python, and Jupyter Notebooks

You'll prototype internal data applications and tools (Streamlit, Lightdash, Jupyter)

You'll ensure data quality and reliability throughout the lifecycle

You'll collaborate with product, technology, commercial and strategy teams to deliver high-impact insights and tools

Data Modelling Experience: Proficiency in using dbt (ideally) for data modelling
Dashboard and Data Product Development: Experience in creating data dashboards and developing data products.
Collaborative Projects: Experience working on collaborative projects with business teams and familiarity with agile or similar methodologies.
Autonomous Problem-Solving: Ability to work independently, scope problems, and deliver pragmatic solutions.
Data Lifecycle Expertise: Versatility in handling the entire data lifecycle, from ingestion to visualisation and presentation.
Tool Building: Passion for creating robust and usable tools to enhance team efficiency.
Data Analysis Skills: Proficiency in SQL, python, pandas/numpy, Databricks/Jupyter Notebooks, and experience with large datasets in production environments.
GenAI: Experience implementing agentic workflows (nice to have)
Curiosity and Drive: Self-motivated with a strong desire to learn and improve without lots of help and support.
Growth mindset: Learns fast and is enthusiastic about learning new technologies
Time Management: Ability to manage multiple projects simultaneously in a fast-paced environment.

dbt for data modelling

Lightdash and Databricks AI/BI Dashboards as business intelligence tools

Databricks Delta Lake for data lake and warehouse storage and querying

python as our main programming language

Jupyter and Jupyter Hub for notebook analytics and collaboration

Circle CI for continuous deployment

AWS cloud infrastructure

Kubernetes for data services and task orchestration

Airflow for job scheduling and tracking

Parquet and Delta file formats on S3 for data lake storage

Streamlit for data applications

The projects will be varied and we’re looking for someone who can work autonomously and proactively to scope problems and solve and deliver pragmatic solutions