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Octopus Energy, France's 5th largest energy provider in just 10 years, is seeking an experienced Senior Analytical Engineer to join the cross-functional data team. The data function comprises approximately 15 data analysts, data scientists, and data engineers embedded across business domains, with a focus on building solid, shared, and reliable foundations.
You will work on analytical foundations, the semantic layer, and data governance in a role that bridges business needs and other data practitioners. Your primary responsibilities include:
**Data Modeling & Semantic Layer:**
- Design, develop, and maintain shared data models serving business needs (particularly financial) and leadership
- Serve as technical reference point for financial and energy procurement teams
- Structure and organize data governance to ensure a single source of truth
**Data Quality & Standards:**
- Ensure data model quality through best practice dissemination and quality monitoring
- Prevent redundancies and technical debt accumulation to maintain clean lineage
- Manage incidents on critical models
**Community Development & Upskilling:**
- Lead or co-lead training, coaching, and routines for data teams
- Drive AI transition of the stack through skill-building, demonstrations, and use cases
- Ensure code quality via PR reviews on dbt models and SQL queries from other data practitioners
**International Coordination:**
- Ensure consistency and relay common practices across Octopus Energy group
- Contribute to improvements in shared models
The role is hybrid (3 days in-office, 2 days remote) based in Paris. You'll have genuine cross-functional impact, influencing data decisions across Octopus Energy France's data community.
**Requirements:**
- Minimum 5 years of experience in analytical engineering, analytical data engineering, or analytics with strong technical orientation
- Advanced dbt mastery: real-world project experience with structure, documentation, and testing
- Expert SQL: capable of optimizing complex queries on modern data warehouses (BigQuery, Snowflake, Databricks, or equivalent)
- Comfortable with Python for automation and analytical scripts, following development best practices
- Proficiency with data visualization tools and programmatic management practices (e.g., dashboard-as-code)
- Strong knowledge of analytical architecture patterns: Kimball, Data Vault, Medallion, or hybrid—understanding the reasoning behind each choice
- Experience with data quality management
- Academic background in statistics, mathematics, economics, specialized data diploma, or engineering school with strong data aptitude
- Fluent English (spoken and written) for international team collaboration
- Pedagogical mindset and desire to upskill others to avoid silos
- Comfortable in decentralized environments, persuading through work quality and clear recommendations
- Thrives in dynamic environments with changing needs
Tech stack: Lightdash and Streamlit (visualization), dbt (modeling), Databricks on AWS (lakehousing), Airflow (orchestration), Git (code), Claude Code/Copilot/Gemini (AI).
