Lead Data Analyst - Commercial Analytics

Octopus Energy

London (GB), United Kingdom

Full Time

Posted March 9, 2026

Energy Management

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Job Description

In just 10 years, Octopus Energy has evolved from a disruptive challenger into the UK’s largest energy retailer and a well-loved brand, serving more than 8 million customers.

Key Responsibilities

Own end-to-end pricing operations for domestic tariffs, including launches, quarterly price changes, margin reporting and intelligence, and ensuring regulatory / price cap compliance for millions of customers.
Drive pricing strategy and optimisation through competitor intelligence, market analysis, and data-driven recommendations to the Senior Leadership Team.
Own and evolve commercial reporting pipelines across customer switching, sales activity from all channels, marketing campaigns, retention and competitor insight.
Deliver growth and customer insight, including key metric reporting, funnel analysis, customer forecasting, and retention initiatives.
Set priorities, coordinate and review the work of a small, high-performance team of data analysts.
Partner with Commercial, Sales, Marketing, Energy Markets, Flexibility, Gross Margin and Strategic Finance teams to provide customer forecasting inputs, KPI reporting, margin analysis and strategic support.
Contribute to and collaborate with our global working groups to ensure aligned reporting and shared analytics projects.
Champion data best practices and continuous improvement in analytics engineering, tools and automated processes.

Requirements

Hands-on expertise with modern data platforms and analytical tools (especially SQL and python - see our full stack below).
Strong commercial acumen, preferably in pricing, margin optimisation, and/or growth analytics.
Proven experience mentoring and developing data professionals.
Strong communication skills to influence non-technical stakeholders and senior leadership.
A track record of delivering actionable insights that drive measurable business impact.
Python, pandas and SQL in Jupyter notebooks for analysis
dbt and Databricks data platform with Delta Lake
Lightdash as our BI tool and semantic layer
Streamlit for interactive data applications
Airflow for orchestration
Kubernetes for application deployment
CI/CD with GitHub and CircleCI
Infrastructure on AWS, deployed with Terraform / Spacelift